His areas of research include Human-Computer Interaction (HCI, CSCW), Learning Analytics, Artificial Intelligence (AIED, EDM) and Collaborative Learning (CSCL).
His research work is focused on bringing data science and artificial intelligence intho physical learning spaces and to support collocated teamwork skills development. For this, he works with emerging technologies such as interactive surfaces and tabletops, Internet of Things sensors, computer vision algorithms, VR and AR devices, and data visualisation and dashboard tools.
Read his most recent PUBLICATIONS
Australian Research Council (ARC) assesor
Member of the Association for Computing Machinery (ACM)
Member of the Society of Learning Analytics Research (SoLAR)
Member of the International Society of the Learning Sciences (ISLS)
Member of the International Educational Data Mining Society (IEDMS)
Can supervise: YES
Human-Computer Interaction, IoT, Surface Computing, Computer-Supported Collaborative Learning, Orchestration Technology, Learning Analytics, Artificial Intelligence, Educational Data Mining and Data Science.
Roberto Martinez-Maldonado has more than 10 years of teaching experience in Universities of in Mexico and in Australia.
His teaching experience extends across Computer Science, Data Visualisation and Software Engineering.
He is the Lecturer and Subject Soordinator of Data Visualisation and Narratives (36140) in the Masters in Data Science and Innovation (MDSI).
Hernández-Leo, D, Martinez-Maldonado, R, Pardo, A, Muñoz-Cristóbal, JA & Rodríguez-Triana, MJ 2019, 'Analytics for learning design: A layered framework and tools', British Journal of Educational Technology, vol. 50, no. 1, pp. 139-152.View/Download from: UTS OPUS or Publisher's site
© 2018 British Educational Research Association The field of learning design studies how to support teachers in devising suitable activities for their students to learn. The field of learning analytics explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and fragmented work exploring the active role that data analytics can play in supporting design for learning. This paper builds on previous research to propose a framework (analytics layers for learning design) that articulates three layers of data analytics—learning analytics, design analytics and community analytics—to support informed decision-making in learning design. Additionally, a set of tools and experiences are described to illustrate how the different data analytics perspectives proposed by the framework can support learning design processes.
Martinez-Maldonado, R, Kay, J, Buckingham Shum, SJ & Yacef, K 2019, 'Collocated Collaboration Analytics: Principles and Dilemmas for Mining Multimodal Interaction Data', Human-Computer Interaction, vol. 34, no. 1, pp. 1-50.View/Download from: UTS OPUS or Publisher's site
Copyright © 2017 Taylor & Francis Group, LLC Learning to collaborate effectively requires practice, awareness of group dynamics, and reflection; often it benefits from coaching by an expert facilitator. However, in physical spaces it is not always easy to provide teams with evidence to support collaboration. Emerging technology provides a promising opportunity to make collocated collaboration visible by harnessing data about interactions and then mining and visualizing it. These collocated collaboration analytics can help researchers, designers, and users to understand the complexity of collaboration and to find ways they can support collaboration. This article introduces and motivates a set of principles for mining collocated collaboration data and draws attention to trade-offs that may need to be negotiated en route. We integrate Data Science principles and techniques with the advances in interactive surface devices and sensing technologies. We draw on a 7-year research program that has involved the analysis of six group situations in collocated settings with more than 500 users and a variety of surface technologies, tasks, grouping structures, and domains. The contribution of the article includes the key insights and themes that we have identified and summarized in a set of principles and dilemmas that can inform design of future collocated collaboration analytics innovations.
Palominos, E, Levett-Jones, T, Power, T & Martinez-Maldonado, R 2019, 'Healthcare students' perceptions and experiences of making errors in simulation: An integrative review.', Nurse education today, vol. 77, pp. 32-39.View/Download from: UTS OPUS or Publisher's site
BACKGROUND:Research literature suggests that learning from mistakes facilitates news insights and leads to professional development. The significant growth in the use of simulation-based learning is premised on the understanding that in this context learners can make and learn from their errors without negatively impacting real patients. However, studies also suggest that making errors can be emotionally detrimental to learners. Given these contradictory findings, this literature review explores learners' views about this phenomenon. OBJECTIVE:The objective of this integrated review was to explore healthcare students' perceptions of making errors during simulation-based learning experiences. DESIGN:Whittemore and Knafl's framework for integrated reviews was used to structure this review. DATA SOURCES:Five electronic databases MEDLINE, CINAHL, PsycINFO, ProQuest, and SCOPUS and the search engine Google Scholar were searched. The initial terms used were nursing students, medical students, health professionals, error*, mistake*, and simulation. METHODS:The original search resulted in 2317 potential records. After screening against the inclusion/exclusion criteria, 11 articles were critically appraised using The Critical Appraisal Skills Program (CASP) checklist and were included in the review. RESULTS:The two overarching themes to emerge from the analysis were the impact of errors on learners and the impact of errors on learning. CONCLUSION:Despite the negative feelings experienced by some students regarding making mistakes in simulation, there were key factors that moderated the impact of these feelings and transformed the errors into learning opportunities. These included: the provision of a safe learning environment where constructive feedback was provided by skilled educators, and where students were supported to take responsibility for their mistakes. Although the findings suggest that making mistakes in simulation-based learning can be beneficial, optimising l...
Carvalho, L, Freeman, CG, Kearney, A, Mentis, M & Martinez-Maldonado, R 2018, 'Spaces of inclusion and belonging: The learning imaginaries of doctoral students in a multi-campus and distance university', Australasian Journal of Educational Technology, vol. 34, no. 6, pp. 41-52.View/Download from: UTS OPUS or Publisher's site
© Australasian Journal of Educational Technology 2018. Doctoral studies are often described as solitary and challenging endeavors, dependent on candidates' highly developed skills, self-driven nature, and commitment to engage in years of research activity. A range of university initiatives are specially crafted to support higher research degree students, for example, through digital and physical resources, workshops, group gatherings, and others. Our project examines what constitutes significant places for learning and experiences of inclusion amongst doctoral students, and ways of capturing and sharing these experiences with those learning at distance and on university campuses. Our focus is on connections between social values and the built environment, and on developing ways of expressing these values through students' representations of places for learning. This paper reports on interviews with doctoral students' discussing their connections to on-campus and distance places for learning - within the digital and physical landscapes of a multi-campus university, with provision for both, internal and distance students. Our findings reveal the ways doctoral students navigate the digital and physical realms of university spaces, the places they inhabit and value, their attachments to things, and how these, in turn, influence their feelings of inclusion, belonging, and learning purpose.
Munoz-Cristobal, JA, Hernandez-Leo, D, Carvalho, L, Martinez-Maldonado, R, Thompson, K, Wardak, D & Goodyear, P 2018, '4FAD: A framework for mapping the evolution of artefacts in the learning design process', AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY, vol. 34, no. 2, pp. 16-34.View/Download from: UTS OPUS or Publisher's site
Martinez-Maldonado, R, Goodyear, P, Carvalho, L, Thompson, K, Hernandez-Leo, D, Dimitriadis, Y, Prieto, LP & Wardak, D 2017, 'Supporting collaborative design activity in a multi-user digital design ecology', Computers in Human Behavior, vol. 71, pp. 327-342.View/Download from: UTS OPUS or Publisher's site
© 2017 Elsevier Ltd Across a broad range of design professions, there has been extensive research on design practices and considerable progress in creating new computer-based systems that support design work. Our research is focused on educational/instructional design for students’ learning. In this sub-field, progress has been more limited. In particular, neither research nor systems development have paid much attention to the fact that design is becoming a more collaborative endeavor. This paper reports the latest research outcomes from R & D in the Educational Design Studio (EDS), a facility developed iteratively over four years to support and understand collaborative, real-time, co-present design work. The EDS serves to (i) enhance our scientific understanding of design processes and design cognition and (ii) provide insights into how designers’ work can be improved through appropriate technological support. In the study presented here, we introduced a complex, multi-user, digital design tool into the existing ecology of tools and resources available in the EDS. We analysed the activity of four pairs of ‘teacher-designers’ during a design task. We identified different behaviors - in reconfiguring the task, the working methods and toolset usage. Our data provide new insights about the affordances of different digital and analogue design surfaces used in the Studio.
Clayphan, A, Martinez-Maldonado, R, Tomitsch, M, Atkinson, S & Kay, J 2016, 'An In-the-Wild Study of Learning to Brainstorm: Comparing Cards, Tabletops and Wall Displays in the Classroom', INTERACTING WITH COMPUTERS, vol. 28, no. 6, pp. 788-810.View/Download from: UTS OPUS or Publisher's site
Martinez-Maldonado, R, Clayphan, A & Kay, J 2015, 'Deploying and Visualising Teacher’s Scripts of Small Group Activities in a Multi-Surface Classroom Ecology: a study in-the-wild', Computer Supported Cooperative Work, vol. 24, no. 2-3, pp. 177-221.View/Download from: UTS OPUS or Publisher's site
There is a fast growing interest in the use of interactive surfaces in collaborative learning contexts. These devices hold the promise to enrich a typical collocated class by enabling learners to interact with digital content while maintaining face-to-face mutual awareness. However, little has been done to help teachers deploy and monitor the learning scripts for their planned small group activities in a classroom enhanced with these kinds of devices. We present an approach for deploying and visualising the teacher’s script for small group idea generation and problem solving activities in a multi-surface classroom ecology that is composed of multiple interactive tabletops, public vertical displays and a teacher’s dashboard. We frame our study by drawing on design guidelines for classrooms with multiple interactive surfaces and combine these with principles of scripting and orchestration of learning activities. The paper presents the results and experiences of the implementation of our approach, in an authentic deployment of our classroom ecology, held over 8 weeks in a semester, involving 150 university students and 4 teachers. The paper concludes with remarks about the strengths and shortcomings of our approach, to be taken into account by learning practitioners and designers.
Martinez-Maldonado, R, Clayphan, A, Yacef, K & Kay, J 2015, 'MTFeedback: providing notifications to enhance teacher awareness of small group work in the classroom', IEEE Transactions on Learning Technologies, vol. 8, no. 2, pp. 187-200.View/Download from: UTS OPUS or Publisher's site
The teacher has very important roles in the classroom, particularly as manager of most resources for learning activities and
in providing timely feedback that can enhance learning. But teachers need to be aware of students’ achievements and weaknesses to
decide how to time feedback. We present MTFeedback, a system that harnesses the new affordances of interactive tabletops to
generate automatic notifications about small group collaborative tasks for the teacher in real-time. We deployed the system on a
teacher’s hand-held dashboard, which supports orchestration of a multi-tabletop environment, the MTClassroom. We validated our
approach in authentic (in-the-wild) classroom activities, with 95 higher education students and three teachers across two sets of six
classroom sessions. We evaluated the impact of presenting notifications on feedback that teachers provided to students. The
notifications were based on qualitative comparisons of students’ artefacts against a representation of both expert knowledge and a
set of common misconceptions. We demonstrate that our approach can successfully be deployed in the classroom to generate
notifications that help the teacher direct their attention more effectively to provide relevant feedback to their students in small group
Martinez-Maldonado, R, Pardo, A, Mirriahi, N, Yacef, K, Kay, J & Clayphan, A 2015, 'LATUX: an Iterative Workflow for Designing, Validating and Deploying Learning Analytics Visualisations', Journal of Learning Analytics, vol. 2, no. 3, pp. 9-39.View/Download from: UTS OPUS or Publisher's site
Designing, validating, and deploying learning analytics tools for instructors or
students is a challenge that requires techniques and methods from different disciplines, such as
software engineering, human–computer interaction, computer graphics, educational design, and
psychology. Whilst each has established its own design methodologies, we now need
frameworks that meet the specific demands of the cross-disciplinary space defined by learning
analytics are needed. In particular, LAK needs a systematic workflow for creating tools that truly
underpin the learning experience. In this paper, we present a set of guiding principles and
recommendations derived from the LATUX workflow. This is a five-stage workflow to design,
validate, and deploy awareness interfaces in technology-enabled learning environment. LATUX is
based on well-established design processes for creating, testing, and re-designing user interfaces.
We extend existing approaches by integrating the pedagogical requirements needed to guide the
design of learning analytics visualizations that can inform pedagogical decisions or intervention
strategies. We illustrate LATUX in a case study of a classroom with collaborative activities. Finally,
the paper proposes a research agenda to support designers and implementers of learning
Martinez-Maldonado, R, Yacef, K & Kay, J 2015, 'TSCL: A conceptual model to inform understanding of collaborative learning processes at interactive tabletops', International Journal of Human-Computer Studies, vol. 83, pp. 62-82.View/Download from: Publisher's site
Emerging systems for tabletop interaction have the potential to support small groups of students in collaborative learning activities. We argue that these devices have the potential to support learning by exploiting the interaction data that they can capture. The capture, analysis and presentation of these data can provide new ways to gain understanding of the collaborative processes. This is particularly important for teachers at two levels. First, they can gain a deeper level of awareness of the progress of individual students and groups in their class and, based on this, make real-time informed decisions. Second, they can do post-hoc reflection and analyse aspects of the class. This paper presents Tabletop-Supported Collaborative Learning (TSCL), a conceptual model that provides foundations for building tabletop-based systems that can inform understanding of the collaborative learning process. The model provides guidance for building the infrastructure to: (i) capture traces of student activity; (ii) exploit these through data analytics techniques; and (iii) provide useful information about the collaborative processes. We illustrate the usefulness of TSCL in its use to create a learning environment that was evaluated in two studies conducted in tertiary education contexts. The first was a laboratory study, where 60 students in 20 groups worked on a concept mapping task, with data from their interaction used to create visualisations of the group processes. The second study was conducted in-the-wild, involving 140 students, working in 8 class sessions.
Thompson, K, Carvalho, L, Aditomo, A, Dimitriadis, Y, Dyke, G, Evans, MA, Khosronejad, M, Martinez-Maldonado, R, Reimann, P & Wardak, D 2015, 'The synthesis approach to analysing educational design dataset: Application of three scaffolds to a learning by design task for postgraduate education students', British Journal of Educational Technology, vol. 46, no. 5, pp. 1020-1027.View/Download from: UTS OPUS or Publisher's site
The aims of the Synthesis and Scaffolding Project were to understand: the role of specific scaffolds in relation to the activity of learners, and the activity of learners during a collaborative design task from multiple perspectives, through the collection and analysis of multiple streams of data and the adoption of a synthesis approach to the research. The Synthesis Approach to Analysing Educational Design (SAAED) dataset is comprised of video, audio and image files, transcripts of the discourse, as well as copies of physical artefacts generated by three groups of three postgraduate education students during a 90-minute design session. The data were collected in January 2013. Each group was given a different scaffold related to the design process, the social interactions or the use of the tools available to the participants. Researchers interested in analysing the SAAED are required to sign a collaborator agreement to become part of the project team.
Martinez-Maldonado, R, Dimitriadis, Y, Martinez-Mones, A, Kay, J & Yacef, K 2013, 'Capturing and analysing verbal and physical collaborative learning interactions at an enriched interactive tabletop', International Journal of Computer-Supported Collaborative Learning, vol. 8, no. 4, pp. 455-485.View/Download from: UTS OPUS or Publisher's site
Interactive tabletops can be used to provide new ways to support face-to-face collaborative learning. A little explored and somewhat hidden potential of these devices is that they can be used to enhance teachers’ awareness of students’ progress by exploiting captured traces of interaction. These data can make key aspects of collaboration visible and can highlight possible problems. In this paper, we explored the potential of an enriched tabletop to automatically and unobtrusively capture data from collaborative interactions. By analyzing that data, there was the potential to discover trends in students’ activity. These can help researchers, and eventually teachers, to become aware of the strategies followed by groups. We explored whether it was possible to differentiate groups, in terms of the extent of collaboration, by identifying the interwoven patterns of students’ speech and their physical actions on the interactive surface. The analysis was validated on a sample of 60 students, working in triads in a concept mapping learning activity. The contribution of this paper is an approach for analyzing students’ interactions around an enriched interactive tabletop that is validated through an empirical study that shows its operationalization to extract frequent patterns of collaborative activity.
Martinez-Maldonaldo, R, Buckingham-Shum, S, Schneider, B, Charleer, S, Klerkx, J & Duval, E, 'Learning Analytics for Natural User Interfaces', Journal of Learning Analytics, vol. 4, no. 1, pp. 24-57.View/Download from: Publisher's site
Thompson, K, Alhadad, S, Buckingham Shum, S, Howard, S, Knight, S, Martinez-Maldonado, R & Pardo, A 2019, 'Connecting expert knowledge in the design of classroom learning experiences' in Lodge, J, Cooney Horvath, J & Corrin, L (eds), Learning analytics in the classroom: Translating learning analytics research for teachers, Routledge.View/Download from: UTS OPUS
Rosé, CP, Martínez-Maldonado, R, Hoppe, HU, Luckin, R, Mavrikis, M, Porayska-Pomsta, K, McLaren, B & du Boulay, B 2018, 'Preface', pp. V-VI.
Rosé, CP, Martínez-Maldonado, R, Hoppe, HU, Luckin, R, Mavrikis, M, Porayska-Pomsta, K, McLaren, B & du Boulay, B 2018, 'Preface', pp. V-VI.
Dias Pereira Dos Santos, A, Tang, LM, Loke, L & Martinez-Maldonado, R 2018, 'You are off the beat! Is accelerometer data enough for measuring dance rhythm?', ACM International Conference Proceeding Series, International Conference on Movement and Computing, ACM, Genoa, Italy.View/Download from: UTS OPUS or Publisher's site
© 2018 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery. Rhythm is the most basic skill for people learning to dance. Beginners need practice but also close coaching and constant feedback. However, in most dance classes teachers often find challenging to provide attention to each student. A possible solution to this problem would be to automate the provision of feedback to students by objectively assessing rhythm from their movement data. But how effective would a fully automated approach be compared to dance experts in evaluating dance performance? We conducted a study aimed at exploring this by ?easuring' dance rhythm from accelerometer data streams and contrasting the algorithm results with expert human judgement.We developed RiMoDe, an algorithm that tracks bodily rhythmic skills, and gathered a dataset that includes 282 independent evaluations made by expert dance teachers on 94 dance exercises performed by 7 dance students. Our findings revealed major gaps between a purely algorithmic approach and how experts evaluate dance rhythm.We identified 6 themes that are important when assessing rhythm. We discuss how these themes should be considered and incorporated into future systems aimed at supporting people learning to dance.
Giannakos, M, Sharma, K, Martinez-Maldonado, R, Dillenbourg, P & Rogers, Y 2018, 'Learner-computer interaction', ACM International Conference Proceeding Series, Nordic Conference on Human-Computer Interaction, ACM, Oslo, Norway, pp. 968-971.View/Download from: UTS OPUS or Publisher's site
© 2018 Copyright is held by the owner/author(s). Learner-Computer Interaction (LCI) research addresses the design, development and use of interactive technologies to support and amplify human learning. LCI is based on the rationale that learning while interacting with technology is a complex, multi-layered phenomenon, thus, designing the conditions for engaging in meaningful learning is vital in the 21st century, yet, it remains a challenging process. LCI developments are expected to contribute towards a coherent new, high-impact way of understanding and building learner-centered interaction concepts to support the design of future learning environments. LCI provides an interdisciplinary playground for researchers and professionals across all areas of learning technologies, psychology, learning science and human-computer interaction (HCI), with an ultimate objective of providing a forum at the intersection of these topical areas. LCI aims to develop a critical discussion, debate and co-development of ideas and approaches about the next generation of learning environments and their interaction design capacities, the form of these capacities and the way they can be identified, utilized and enhanced to help us improve the contemporary learning technologies and users' learning experience.
Martinez-Maldonado, R, Echeverria, V, Prieto, LP, Rodriguez-Triana, MJ, Spikol, D, Curukova, M, Mavrikis, M, Ochoa, X & Worsley, M 2018, '2nd Crossmmla: Multimodal learning analytics across physical and digital spaces', CEUR Workshop Proceedings.View/Download from: UTS OPUS
© 2018 CEUR-WS. All Rights Reserved. Students’ learning is ubiquitous. It happens wherever the learner is rather than being constrained to a specific physical or digital learning space (e.g. the classroom or the institutional LMS respectively). A critical question is: how to integrate and coordinate learning analytics to provide continued support to learning across physical and digital spaces? CrossMMLA is the successor to the Learning Analytics Across Spaces (CrossLAK) and MultiModal Learning Analytics (MMLA) series of workshops that were merged in 2017 after successful cross-pollination between the two communities. Although it may be said that CrossLAK and MMLA perspectives follow different philosophical and practical approaches, they both share a common aim. This aim is: deploying learning analytics innovations that can be used across diverse authentic learning environments whilst learners feature various modalities of interaction or behaviour.
Martinez-Maldonado, R, Echeverria, V, Santos, OC, Dos Santos, ADP & Yacef, K 2018, 'Physical learning analytics: A multimodal perspective', ACM International Conference Proceeding Series, pp. 375-379.View/Download from: UTS OPUS or Publisher's site
© 2018 Association for Computing Machinery. The increasing progress in ubiquitous technology makes it easier and cheaper to track students’ physical actions unobtrusively, making it possible to consider such data for supporting research, educator interventions, and provision of feedback to students. In this paper, we reflect on the underexplored, yet important area of learning analytics applied to physical/motor learning tasks and to the physicality aspects of ‘traditional’ intellectual tasks that often occur in physical learning spaces. Based on Distributed Cognition theory, the concept of Internet of Things and multimodal learning analytics, this paper introduces a theoretical perspective for bringing learning analytics into physical spaces. We present three prototypes that serve to illustrate the potential of physical analytics for teaching and learning. These studies illustrate advances in proximity, motion and location analytics in collaborative learning, dance education and healthcare training.
Dias Pereira Dos, A, Loke, L & Martinez-Maldonado, R 2018, 'Exploring video annotation as a tool to support dance teaching', Proceedings of the 30th Australian Conference on Computer-Human Interaction, Australian Conference on Computer-Human Interaction, ACM, Melbourne, Australia, pp. 448-452.View/Download from: UTS OPUS or Publisher's site
© 2018 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery. It is challenging for dance teachers to provide feedback to all students learning to dance. This is a common problem in large social dance classes, where the teacher do not have time to reflect before giving feedback. One possible way to address this is to allow dance instructors, peers, or students themselves to assess students' performance using video recordings. In this paper, we explore the use of a video annotation tool by dance teachers. We focused on a particular style of partner dance: Forró. We followed a three-step process to design and validate the video annotation tool, which includes: 1) interviewing dance teachers to understand the context and their needs; 2) asking teachers to assess video recordings of students dancing to capture their'vocabulary'; and 3) developing the video annotation tool. We conducted semi-structured interviews with four dance teachers to understand how the tool can support dance teaching. The contribution of this paper is the exploration of the use of video annotation as a tool to support dance teaching. The paper discusses a series of insights gained by teachers as a result of using our annotation tool which was carefully crafted based on dance education foundations and the vocabulary elicited from experienced dance teachers.
Echeverria, V, Martinez-Maldonado, R, Granda, R, Chiluiza, K, Conati, C & Shum, SB 2018, 'Driving data storytelling from learning design', Proceedings of the 8th International Conference on Learning Analytics and Knowledge, International Conference on Learning Analytics and Knowledge, ACM, Sydney, New South Wales, Australia, pp. 131-140.View/Download from: UTS OPUS or Publisher's site
© 2018 Association for Computing Machinery. Data science is now impacting the education sector, with a growing number of commercial products and research prototypes providing learning dashboards. From a human-centred computing perspective, the end-user’s interpretation of these visualisations is a critical challenge to design for, with empirical evidence already showing that ‘usable’ visualisations are not necessarily effective from a learning perspective. Since an educator’s interpretation of visualised data is essentially the construction of a narrative about student progress, we draw on the growing body of work on Data Storytelling (DS) as the inspiration for a set of enhancements that could be applied to data visualisations to improve their communicative power. We present a pilot study that explores the effectiveness of these DS elements based on educators’ responses to paper prototypes. The dual purpose is understanding the contribution of each visual element for data storytelling, and the effectiveness of the enhancements when combined.
Echeverria, V, Martinez-Maldonado, R, Power, T, Hayes, C & Shum, SB 2018, 'Where is the Nurse? Towards automatically visualising meaningful team movement in healthcare education', 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II (LNCS), International Conference on Artificial Intelligence in Education, Springer, London, United Kingdom, pp. 74-78.View/Download from: UTS OPUS or Publisher's site
© Springer International Publishing AG, part of Springer Nature 2018. Providing immediate, effective feedback on team and individual performance in healthcare simulations is a challenging task for educators, such is their complexity. Focusing on emergency procedures on patient manikins, our prior work has demonstrated the feasibility of using multimodal data capture and analysis to generate visualisations of student movement, talk and treatment actions. The limitation to date has been the need for manual steps in the analytic workflow. This paper documents how we have automated several key steps, using new technologies, which were piloted during a nursing simulation. Combining role-based nurses’ movement data with high fidelity manikin logs, we have implemented a zone-based classification model, and are able to automatically visualise movements within an emergency response team, providing the data needed to design near real-time feedback for both educators and students.
Martinez-Maldonado, R, Anderson, TD, Silva Feraud, I & Buckingham Shum, S 2018, 'Making learning journeys visible: Towards supporting collective reflection on graduate attributes', Proceedings of International Conference of the Learning Sciences, ICLS, International Society of the Learning Sciences, London, UK, pp. 941-944.View/Download from: UTS OPUS
© ISLS. Although some computer-based systems exist to facilitate the management of capstone projects, it is not really clear how learners can be supported to reflect on the connection between their (past and ongoing) learning experiences, and the graduate attributes (GAs) they are intended to develop. This paper proposes a technological infrastructure, and the epistemic and social scaffolding, for students to collectively reflect on how each of their learning products generated across different units of study contribute to the development of their GAs, in light of a final capstone project. We illustrate the feasibility of our approach through the authentic deployment of the toolset in an immersive environment for supporting teams of final year students to reflect on their GAs development.
Prieto-Alvarez, CG, Martinez-Maldonado, R & Shum, SB 2018, 'Mapping learner-data journeys: Evolution of a visual co-design tool', OzCHI '18 Proceedings of the 30th Australian Conference on Computer-Human Interaction, Australian Conference on Computer-Human Interaction, ACM, Australia, pp. 205-214.View/Download from: UTS OPUS or Publisher's site
© 2018 Copyright held by the owner/author(s). In this paper we present a three-phase process for crafting Learner-Data Journey maps and using them as communication tools to involve other stakeholders in the co-design of a data-intensive educational tool. The three phases in this process are i) scaffolding groups of learners to collaboratively co-create a Learner-Data Journey based on their own experience, ii) distilling key insights from these journey maps, and iii) providing the means for multiple stakeholders to integrate and synthesise key insights from these journey maps to suggest design requirements. We illustrate the process and the kind of tools that can support the co-creation of Learner-Data Journeys in two educational scenarios where learners have become partners of their own 'surveillance'.
Clayphan, AJ, Martinez-Maldonado, R & Kay, J 2017, 'A student-facing dashboard for supporting sensemaking about the brainstorm process at a multi-surface space', ACM International Conference Proceeding Series, Australian Conference on Computer-Human Interaction, ACM, Brisbane, Queensland, Australia, pp. 49-58.View/Download from: UTS OPUS or Publisher's site
© 2017 Association for Computing Machinery. All rights reserved. We developed a student-facing dashboard tuned to support posthoc sensemaking in terms of participation and group effects in the context of collocated brainstorming. Grounding on foundations of small-group collaboration, open learner modelling and brainstorming at large interactive displays, we designed a set of models from behavioural data that can be visually presented to students. We validated the effectiveness of our dashboard in provoking group reflection by addressing two questions: (1) What do group members gain from studying measures of egalitarian contribution? and (2) What do group members gain from modelling how they sparked ideas off each other? We report on outcomes from a study with higher education students performing brainstorming. We present evidence from i) descriptive quantitative usage patterns; and ii) qualitative experiential descriptions reported by the students. We conclude the paper with a discussion that can be useful for the community in the design of collective reflection systems.
Dos Santos, ADP, Yacef, K & Martinez-Maldonado, R 2017, 'Forró Trainer: Automated Feedback for Partner Dance Learning', UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, Conference on User Modeling, Adaptation and Personalization, ACM, Bratislava, Slovakia, pp. 103-104.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. In partner dance classes, teachers typically manage several students at the same time. For that reason, the amount of feedback provided in class is quite limited and students do not have many resources to get other feedback. In this demo paper, we present Forró Trainer, a tool that allows students to practice dance exercises by themselves, receiving automatically generated feedback about their performance. The system runs on a smartphone app and focuses on a fundamental aspect of dancing: learning to follow the rhythm of the music. The app detects the student's movements, using the mobile's accelerometer, extracts aspects of the rhythm and provides feedback. We present a description of the tool, the mistakes it detects, the automated feedback and the benefits that it may provide for dance students.
Dos Santos, ADP, Yacef, K & Martinez-Maldonado, R 2017, 'Let's Dance: How to build a user model for dance students using wearable technology', UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, Conference on User Modeling, Adaptation and Personalization, ACM, Bratislava, Slovakia, pp. 183-191.View/Download from: UTS OPUS or Publisher's site
©2017 ACM. Motor skill learning is an area where wearable technology and user modelling can be synergistically combined for providing support. In this paper, we explore how a simple accelerometer sensor can be used to capture motion data associated with critical aspects of learning in the context of social dancing. We developed a prototype mobile app that tracks students' motion data whilst they practise dance exercises. This paper describes a set of features, such as rhythm duration, consistency and body motion, which can be automatically tracked and included into a dance student model. These dancing features can be presented back to the students as feedback, in the form of i) summaries, ii) visualisations or iii) narratives. We illustrate the feasibility and potential of modelling these features through a study with beginner students taking dance classes during three weeks.
Echeverria, V, Falcones, G, Castells, J, Martinez-Maldonado, R & Chiluiza, K 2017, 'Exploring on-time automated assessment in a co-located collaborative system', 2017 4th International Conference on eDemocracy and eGovernment, ICEDEG 2017, International Conference on eDemocracy & eGovernment, IEEE, Quito, Ecuador, pp. 273-276.View/Download from: UTS OPUS or Publisher's site
© 2017 IEEE. This research explores the effects of providing on-time automated assessment in a co-located collaborative system for Entity-Relationship design. In addition, students' perceptions about the validity and usefulness of this automated assessment, and its potential for reflection were analyzed. Thirty undergraduate students from computer science participated in the study, a quasi-experimental pre-post test design was conducted. Short quizzes for measuring students' learning performance were used and the perceptions of students were gathered by means of questionnaires. Results showed that on-time assessment positively affected students' learning performance in the study. Finally, students perceived that the system assessment is valid and useful and has the potential to generate mechanisms for reflecting about individual learning and group performance. The study concludes with steps for further research.
Gibson, A & Martinez-Maldonado, R 2017, 'That dashboard looks nice, but what does it mean? towards making meaning explicit in learning analytics design', ACM International Conference Proceeding Series, pp. 528-532.View/Download from: UTS OPUS or Publisher's site
© 2017 Association for Computing Machinery. All rights reserved. As learning analytics (LA) systems become more common, teachers and students are often required to not only make sense of the user interface (UI) elements of a system, but also to make meaning that is pedagogically appropriate to the learning context. However, we suggest that the dominant way of thinking about the relationship between representation and meaning results in an overemphasis on the UI, and that re-thinking this relationship is necessary to create systems that can facilitate deeper meaning making. We propose a conceptual view as a basis for discussion among the LA and HCI communities around a different way of thinking about meaning making, specifically that it should be explicit in the design process, provoking greater consideration of system level elements such as algorithms, data structures and information flow. We illustrate the application of the conceptualisation with two cases of LA design in the areas of Writing Analytics and Multi-modal Dashboards.
Martinez-Maldonado, R, Echeverria, V, Yacef, K, Dos Santos, ADP & Pechenizkiy, M 2017, 'How to capitalise on mobility, proximity and motion analytics to support formal and informal education?', CEUR Workshop Proceedings, Multimodal Learning Analytics Workshop & International Learning Analytics and Knowledge Conference, CEUR, Vancouver, Canada, pp. 39-46.View/Download from: UTS OPUS
© 2017, CEUR-WS. All rights reserved. Learning Analytics and similar data-intensive approaches aimed at understanding and/or supporting learning have mostly focused on the analysis of students' data automatically captured by personal computers or, more recently, mobile devices. Thus, most student behavioural data are limited to the interactions between students and particular learning applications. However, learning can also occur beyond these interface interactions, for instance while students interact face-to-face with other students or their teachers. Alternatively, some learning tasks may require students to interact with non-digital physical tools, to use the physical space, or to learn in different ways that cannot be mediated by traditional user interfaces (e.g. motor and/or audio learning). The key questions here are: why are we neglecting these kinds of learning activities? How can we provide automated support or feedback to students during these activities? Can we find useful patterns of activity in these physical settings as we have been doing with computer-mediated settings? This position paper is aimed at motivating discussion through a series of questions that can justify the importance of designing technological innovations for physical learning settings where mobility, proximity and motion are tracked, just as digital interactions have been so far.
Martinez-Maldonado, R, Hernandez-Leo, D, Pardo, A & Ogata, H 2017, '2nd Cross-LAK: Learning analytics across physical and digital spaces', ACM International Conference Proceeding Series, pp. 510-511.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. Student's learning happens where the learner is, rather than being constrained to a single physical or digital environment. It is of high relevance for the LAK community to provide analytics support in blended learning scenarios where students can interact at diverse learning spaces and with a variety of educational tools. This workshop aims to gather the subcommunity of LAK researchers, learning scientists and researchers in other areas, interested in the intersection between ubiquitous, mobile and/or classroom learning analytics. The underlying concern is how to integrate and coordinate learning analytics seeking to understand the particular pedagogical needs and context constraints to provide learning analytics support across digital and physical spaces. The goals of the workshop are to consolidate the Cross-LAK sub-community and provide a forum for idea generation that can build up further collaborations. The workshop will also serve to disseminate current work in the area by both producing proceedings of research papers and working towards a journal special issue.
Prieto, LP, Martínez-Maldonado, R, Spikol, D, Hernández-Leo, D, Rodríguez-Triana, MJ & Ochoa, X 2017, 'Editorial: Joint Proceedings of the Sixth Multimodal Learning Analytics (MMLA) Workshop and the Second Cross-LAK Workshop', CEUR Workshop Proceedings, pp. 1-3.View/Download from: UTS OPUS
© 2017, CEUR-WS. All rights reserved. Learning is a complex, mostly invisible process that happens across spaces, occurring in the physical world but also increasingly in virtual worlds or web-based spaces. In order to explore what happens in such blended learning experience, there is a need for multiple data sources that bring evidence from these different spaces. The present proceedings bring together two workshops co-located at the Learning Analytics and Knowledge (LAK'17) conference in Vancouver (Canada): the 2nd Cross-LAK and the 6th Multimodal Learning Analytics (MMLA) workshop. The two workshops tackled the analysis of this complexity, from complementary perspectives. Our aim is to promote dialogue and the alignment of these research efforts across both subcommunities. Moreover, this collaboration is the seed of a Special Interest Group (SIG) that will be part of the Society of Learning Analytics Research (SoLAR). The goal of this SIG will be to advance the understanding of the learning process no matter where and how it happens.
Echeverria, V, Martinez-Maldonado, R & Shum, SB 2017, 'Towards data storytelling to support teaching and learning', ACM International Conference Proceeding Series, 29th Australian Conference on Computer-Human Interaction 2017, Brisbane, Queensland, Australia, pp. 347-351.View/Download from: UTS OPUS or Publisher's site
© 2017 Association for Computing Machinery. All rights reserved. Data science is now impacting the educational sector, with a growing number of commercial products and research prototypes providing learning dashboards as feedback for both educators and students. From a human-centred computing perspective, the end-user's interpretation of these visualisations is a critical challenge to design for, with empirical evidence already showing that 'usable' visualisations are not necessarily effective from a teaching and learning perspective. Since an educator's interpretation of visualised data is essentially the construction of a narrative about that student's progress, we draw on the growing body of work on 'Data Storytelling' (DS) as the inspiration for a set of enhancements that could be applied to data visualisations to improve their communicative power. We present a pilot study that explores the effectiveness of these DS elements based on educators' responses to paper prototypes. The dual purpose is understanding the contribution of each visual element for data storytelling, and the effectiveness of the enhancements when combined. The results suggest that DS elements could add clarity, especially when there are multiple possible stories in a complex visualisation.
Echeverria, V, Martinez-Maldonado, R, Chiluiza, K & Shum, SB 2017, 'DBCollab: Automated Feedback for Face-to-Face Group Database Design', 25TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2017), International Conference on Computers in Education, ASIA PACIFIC SOC COMPUTERS IN EDUCATION, Christchurch, New Zealand, pp. 156-165.View/Download from: UTS OPUS
Martinez-Maldonado, R, Buckingham-Shum, S, Pechenizkiy, M, Power, T, Hayes, C & Axisa, C 2017, 'Modelling embodied mobility teamwork strategies in a simulation-based healthcare classroom', UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, Conference on User Modeling, Adaptation and Personalization, ACM, Bratislava, Slovakia, pp. 308-312.View/Download from: UTS OPUS or Publisher's site
©2017 ACM. In many situations, it remains critical for team members to develop strategies to effectively use the space and tools available to complete demanding tasks. However, despite the availability of sensors and analytics for instrumenting physical space, relatively little progress has been made in modelling the embodied dimensions of co-located teamwork. This paper explores an in-The-wild pilot study through which we explore a methodology to model embodied mobility teamwork strategies in the context of healthcare education. We developed the means for tracking, clustering and processing student-nurses' mobility data around a patient manikin. We illustrate the feasibility of our approach by discussing ways to make sense of these data to uncover meaningful trends, and the inherent challenges of applying physical space analytics in authentic settings.
Martinez-Maldonado, R, Power, T, Hayes, C, Abdiprano, A, Vo, T, Axisa, C & Shum, SB 2017, 'Analytics meet patient manikins: Challenges in an authentic small-group healthcare simulation classroom', LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference, International Learning Analytics and Knowledge Conference, ACM, Vancouver, British Columbia, Canada, pp. 90-94.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. Healthcare simulations are hands-on learning experiences aimed at allowing students to practice essential skills that they may need when working with real patients in clinical workplaces. Some clinical classrooms are equipped with patient manikins that can respond to actions or that can be programmed to deteriorate over time. Students can perform assessments and interventions, and enhance their critical thinking and communication skills. There is an opportunity to exploit the students' digital traces that these manikins can pervasively capture to make key aspects of the learning process visible. The setting can be augmented with sensors to capture traces of group interaction. These multimodal data can be used to generate visualisations or feedback for students or teachers. This paper reports on an authentic classroom study using analytics to integrate multimodal data of students' interactions with the manikins and their peers in simulation scenarios. We report on the challenges encountered in deploying such analytics 'in the wild', using an analysis framework that considers the social, epistemic and physical dimensions of collocated group activity.
Martinez-Maldonado, R, Yacef, K, Santos, ADPD, Shum, SB, Echeverria, V, Santos, OC & Pechenizkiy, M 2017, 'Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning', Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017, 2017 IEEE 17th International Conference on Advanced Learning Technologies, IEEE, Timisoara, Romania, pp. 89-91.View/Download from: UTS OPUS or Publisher's site
© 2017 IEEE. A large number of learning tools offering some sort of personalisation features rely mainly on the analysis of logged interactions between students and particular user interfaces. Much less attention has been given to the analysis of physical aspects so often present in 'traditional' intellectual tasks, although these are both important in the full development of a life-long learner. This paper (1) discusses existing literature focused on supporting learning using proximity and location analytics and sensors, and, based on this, (2) illustrates the feasibility and potential of these analytics for teaching and learning through an study in the context of proximity and location analytics in a team-based health simulation classroom.
Pardo, A, Martínez-Maldonado, R, Shum, SB, Schulte, J, McIntyre, S, Gašević, D, Gao, J & Siemens, G 2017, 'Connecting data with student support actions in a course: A hands-on tutorial', ACM International Conference Proceeding Series, pp. 522-523.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. The amount of data extracted from learning experiences has grown at an astonishing pace both in depth due to the increasing variety of data sources, and in breath with courses now being offered to massive student cohorts. However, in this emerging scenario instructors are now facing the challenge of connecting the knowledge emerging from data analysis with the provision of meaningful support actions to students within the context of an instructional design. The objective of this tutorial is to give attendees a set of hypothetical scenarios in which the knowledge extracted from a learning experience needs to be used to provide frequent personalized feedback to students.
Schulte, J, De Mendonca, PF, Martinez-Maldonado, R & Shum, SB 2017, 'Large scale predictive process mining and analytics of university degree course data', ACM International Conference Proceeding Seventh International Learning Analytics & Knowledge Conference, International Learning Analytics & Knowledge Conference, Vancouver, British Columbia, Canada, pp. 538-539.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. For students, in particular freshmen, the degree pathway from semester to semester is not that transparent, although students have a reasonable idea what courses are expected to be taken each semester. An often-pondered question by students is: "what can I expect in the next semester?" More precisely, given the commitment and engagement I presented in this particular course and the respective performance I achieved, can I expect a similar outcome in the next semester in the particular course I selected? Are the demands and expectations in this course much higher so that I need to adjust my commitment and engagement and overall workload if I expect a similar outcome? Is it better to drop a course to manage expectations rather than to (predictably) fail, and perhaps have to leave the degree altogether? Degree and course advisors and student support units find it challenging to provide evidence based advise to students. This paper presents research into educational process mining and student data analytics in a whole university scale approach with the aim of providing insight into the degree pathway questions raised above. The beta-version of our course level degree pathway tool has been used to shed light for university staff and students alike into our university's 1,300 degrees and associated 6 million course enrolments over the past 20 years.
Knight, S, Martinez-Maldonado, R, Gibson, A & Shum, SB 2017, 'Towards mining sequences and dispersion of rhetorical moves in student written texts', ACM International Conference Proceeding Series, International Learning Analytics & Knowledge Conference, ACM, Vancouver, British Columbia, Canada, pp. 228-232.View/Download from: UTS OPUS or Publisher's site
© 2017 ACM. There is an increasing interest in the analysis of both student's writing and the temporal aspects of learning data. The analysis of higher-level learning features in writing contexts requires analyses of data that could be characterised in terms of the sequences and processes of textual features present. This paper (1) discusses the extant literature on sequential and process analyses of writing; and, based on this and our own first-hand experience on sequential analysis, (2) proposes a number of approaches to both pre-process and analyse sequences in whole-texts. We illustrate how the approaches could be applied to examples drawn from our own datasets of 'rhetorical moves' in written texts, and the potential each approach holds for providing insight into that data. Work is in progress to apply this model to provide empirical insights. Although, similar sequence or process mining techniques have not yet been applied to student writing, techniques applied to event data could readily be operationalised to undercover patterns in texts.
Thompson, K, Danielson, A, Gosselin, D, Knight, S, Martinez-Maldonado, R, Parnell, R, Pennington, D, Svoboda-Gouvea, J, Vincent, S & Wheeler, P 2017, 'Designing the EMBeRS Summer School: Connecting Stakeholders in Learning, Teaching and Research', 25TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2017), International Conference on Computers in Education, ASIA PACIFIC SOC COMPUTERS IN EDUCATION, Christchurch, New Zealand, pp. 210-215.View/Download from: UTS OPUS
In this paper, we describe our research investigating design, teaching and learning aspects of the EMBeRS Summer School. In 2016, thirteen graduate Environmental Science students participated in a ten-day Summer School to learn about interdisciplinary approaches to researching socio-environmental systems. Using the Employing Model-Based Reasoning in Socio-Environmental Synthesis (EMBeRS) approach, students learned about wicked problems, team composition, systems thinking and modelling, stakeholder management, and communication. They applied this approach to their own research, as well as to a case study, in order to, ultimately, further the EMBeRS approach in their own institutions. Learning sciences researchers, environmental science instructors and learners collaborated in design, teaching, and learning during the 2016 Summer School in order to co-create and co-configure the tasks, social arrangements, and tools for learning, teaching and design. This paper identifies four examples of connections between the stakeholders (researchers, instructors and learners), the tools that facilitated the connection, and the implications for learning, teaching and design.
Martinez-Maldonado, R 2016, 'Seeing learning analytics tools as orchestration technologies: Towards supporting learning activities across physical and digital spaces', CEUR Workshop Proceedings: Proceedings of the First International Workshop on Learning Analytics Across Physical and Digital Spaces co-located with 6th International Conference on Learning Analytics & Knowledge (LAK 2016), First International Workshop on Learning Analytics Across Physical and Digital Spaces co-located with 6th International Conference on Learning Analytics & Knowledge (LAK 2016), CEUR, Edinburgh, Scotland, pp. 70-73.View/Download from: UTS OPUS
© Copyright 2016 for this paper by its authors.This panel paper proposes to consider the process that learners or educators commonly follow while interacting with learning analytics tools as part of an orchestration loop. This may be particularly valuable to facilitate understanding of the key role that learning analytics may have to provide sustained support to learners and educators. The complexity of learning situations where learning occurs across varied physical spaces and multiple educational tools are involved requires a holistic and practical approach. The proposal is to build on principles of orchestration that can help link technical and theoretical aspects of learning analytics with the practitioner. The panel paper provides: 1) a brief description of the relevance of the notions of orchestration and orchestrable technologies for learning analytics; and 2) the illustration of the orchestration loop as a process followed by learners or educators when they use learning analytics tools.
Martinez-Maldonado, R & Goodyear, P 2016, 'CoCoDeS: Multi-device support for collocated collaborative learning design', Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016, Australian Computer Human Interaction Conference, ACM, Launceston, Tasmania, pp. 185-194.View/Download from: UTS OPUS or Publisher's site
Copyright © 2016 ACM.We propose a novel principled approach and the toolset to support collocated team-based educational design. We scaffold teams of teachers as designers creating rapid high-level course designs. We provide teachers with an ecology of digital and non-digital devices, an embedded design pattern library and a design dashboard. The toolset is situated within a purpose-built educational design studio and includes a set of surface devices that allow teachers to manipulate iconic representations of a course design and get real-time design analytics on selected parameters. The contribution of the paper is a description of the rationale for, implementation and evaluation of, an innovative toolset that sits in an ecology of resources to support collocated educational design.
Martinez-Maldonado, R, Goodyear, P, Kay, J, Thompson, K & Carvalho, L 2016, 'An Actionable Approach to Understand Group Experience in Complex, Multi-surface Spaces', Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, Conference on Human Factors in Computing Systems, ACM, Santa Clara, California, USA, pp. 2062-2074.View/Download from: Publisher's site
There is a steadily growing interest in the design of spaces in which multiple interactive surfaces are present and, in turn, in understanding their role in group activity. However, authentic activities in these multi-surface spaces can be complex. Groups commonly use digital and non-digital artefacts, tools and resources, in varied ways depending on their specific social and epistemic goals. Thus, designing for collaboration in such spaces can be very challenging. Importantly, there is still a lack of agreement on how to approach the analysis of groups' experiences in these heterogeneous spaces. This paper presents an actionable approach that aims to address the complexity of understanding multi-user multi-surface systems. We provide a structure for applying different analytical tools in terms of four closely related dimensions of user activity: the setting, the tasks, the people and the runtime co-configuration. The applicability of our approach is illustrated with six types of analysis of group activity in a multi-surface design studio.
Martinez-Maldonado, R, Pardo, A & Hernández-Leo, D 2016, 'Introduction to cross LAK 2016: Learning analytics across spaces', Proceedings of the First International Workshop on Learning Analytics Across Physical and Digital Spaces co-located with 6th International Conference on Learning Analytics & Knowledge (LAK 2016), First International Workshop on Learning Analytics Across Physical and Digital Spaces co-located with 6th International Conference on Learning Analytics & Knowledge (LAK 2016), CEUR, Edinburgh, Scotland, pp. 1-4.View/Download from: UTS OPUS
For the LAK (Learning Analytics and Knowledge) community, it is highly important to pay attention to the development and deployment of learning analytics solutions for blended learning scenarios where students work at diverse digital and physical learning spaces and interact in different modalities. This workshop has been a first attempt in gathering the sub-community of LAK researchers, learning scientists and researchers from other communities, interested in ubiquitous, mobile and/or face-to-face learning analytics. It was clear for all the attendees that a key concern that has not been deeply explored yet is associated with the mechanisms to integrate and coordinate learning analytics to provide continued support to learning across digital and physical spaces. The two main goals of the workshop were to share perspectives and identify a set of guidelines that could be offered to teachers, researchers or designers to create and connect Learning Analytics solutions according to the pedagogical needs and contextual constraints to provide support across digital and physical learning spaces.
Pardo, A, Jovanovic, J, Mirriahi, N, Dawson, S, Martinez-Maldonado, R & Gaševic, D 2016, 'Generating actionable predictive models of academic performance', Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, International Learning Analytics & Knowledge Conference, ACM, Edinburgh, United Kingdom, pp. 474-478.View/Download from: UTS OPUS or Publisher's site
© 2016 Copyright held by the owner/author(s).The pervasive collection of data has opened the possibility for educational institutions to use analytics methods to improve the quality of the student experience. However, the adoption of these methods faces multiple challenges particularly at the course level where instructors and students would derive the most benefit from the use of analytics and predictive models. The challenge lies in the knowledge gap between how the data is captured, processed and used to derive models of student behavior, and the subsequent interpretation and the decision to deploy pedagogical actions and interventions by instructors. Simply put, the provision of learning analytics alone has not necessarily led to changing teaching practices. In order to support pedagogical change and aid interpretation, this paper proposes a model that can enable instructors to readily identify subpopulations of students to provide specific support actions. The approach was applied to a first year course with a large number of students. The resulting model classifies students according to their predicted exam scores, based on indicators directly derived from the learning design.
Martinez-Maldonado, R, Schneider, B, Charleer, S, Buckingham Shum, S, Klerkx, J & Duval, E 2016, 'Interactive surfaces and learning analytics: data, orchestration aspects, pedagogical uses and challenges', LAK '16 Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, International Learning Analytics & Knowledge Conference, ACM, Edinburgh, United Kingdom, pp. 124-133.View/Download from: UTS OPUS or Publisher's site
The proliferation of varied types of multi-user interactive surfaces (such as digital whiteboards, tabletops and tangible interfaces) is opening a new range of applications in face-to-face (f2f) contexts. They offer unique opportunities for Learning Analytics (LA) by facilitating multi-user sensemaking of automatically captured digital footprints of students' f2f interactions. This paper presents an analysis of current research exploring learning analytics associated with the use of surface devices. We use a framework to analyse our first-hand experiences, and the small number of related deployments according to four dimensions: the orchestration aspects involved; the phases of the pedagogical practice that are supported; the target actors; and the levels of iteration of the LA process. The contribution of the paper is twofold: 1) a synthesis of conclusions that identify the degree of maturity, challenges and pedagogical opportunities of the existing applications of learning analytics and interactive surfaces; and 2) an analysis framework that can be used to characterise the design space of similar areas and LA applications.
Martinez-Maldonado, R, Hernandez-Leo, D, Pardo, A, Suthers, D, Kitto, K, Charleer, S, Aljohani, NR & Ogata, H 2016, 'Cross-LAK: Learning Analytics Across Physical and Digital Spaces', LAK '16 CONFERENCE PROCEEDINGS: THE SIXTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE,, 6th International Conference on Learning Analytics and Knowledge (LAK), ASSOC COMPUTING MACHINERY, Univ Edinburgh, Edinburgh, SCOTLAND, pp. 486-487.
Martinez-Maldonado, R, Anderson, T, Shum, SB & Knight, S 2016, 'Towards supporting awareness for content curation: The case of food literacy and behavioural change', CEUR Workshop Proceedings, Learning Analytics for Learners (LAK-LAL), Central Europe Workshop, Edinburgh, Scotland, pp. 42-46.
Copyright © 2016 for the individual papers by the papers' authors.This paper presents a theoretical grounding and a conceptual proposal aimed at providing support in the initial stages of sustained behavioural change. We explore the role that learning analytics and/or open learner models can have in supporting life-long learners to enhance their food literacy through a more informed curation process of relevant-content. This approach grounds on a behavioural change perspective that identifies i) knowledge, ii) attitudes, and iii) self-efficacy as key factors that will directly and indirectly affect future decisions and agency of life-long learners concerning their own health. The paper offers some possible avenues to start organising efforts towards the use of learning analytics to enhance awareness in terms of: knowledge curation, knowledge sharing and knowledge certainty. The paper aims at triggering discussion about the type of data and presentation mechanisms that may help life-long learners set a stronger basis for behavioural change in the subsequent stages.
Goldin, I, Martinez-Maldonado, R, Walker, E, Kumar, R & Kim, J 2015, '4th Workshop on Intelligent Support for Learning in Groups', ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015, 17th International Conference on Artificial Intelligence in Education (AIED), SPRINGER-VERLAG BERLIN, Univ Natl Educac Distancia, Madrid, SPAIN, pp. 884-884.
Martinez-Maldonado, R, Blanchard, EG, Ogan, A & Gasparini, I 2015, 'Preface', Proceedings of the Workshops at the 17th International Conference on Artificial Intelligence in Education AIED 2015, International Conference on Artificial Intelligence in Education, Madrid, Spain.
Martinez-Maldonado, R, Pardo, A, Mirriahi, N, Yacef, K, Kay, J & Clayphan, A 2015, 'The LATUX workflow: Designing and deploying awareness tools in technology-enabled learning settings', ACM International Conference Proceeding Series, International Learning Analytics & Knowledge Conference, ACM, Poughkeepsie, New York, pp. 1-10.View/Download from: Publisher's site
Designing, deploying and validating learning analytics tools for instructors or students is a challenge requiring techniques and methods from different disciplines, such as software engineering, human-computer interaction, educational design and psychology. Whilst each of these disciplines has consolidated design methodologies, there is a need for more specific methodological frameworks within the cross-disciplinary space defined by learning analytics. In particular there is no systematic workflow for producing learning analytics tools that are both technologically feasible and truly underpin the learning experience. In this paper, we present the LATUX workflow, a five-stage workflow to design, deploy and validate awareness tools in technology-enabled learning environments. LATUX is grounded on a well-established design process for creating, testing and re-designing user interfaces. We extend this process by integrating the pedagogical requirements to generate visual analytics to inform instructors' pedagogical decisions or intervention strategies. The workflow is illustrated with a case study in which collaborative activities were deployed in a real classroom.
Thompson, K, Martinez-Maldonado, R, Wardak, D, Goodyear, P & Carvalho, L 2015, 'Analysing F2F collaborative design and learning: Experiences in a design studio', CEUR Workshop Proceedings, Orchestrated Collaborative Classroom Workshop, CEUR, Gothenburg, Sweden, pp. 25-29.
This paper presents our proposed methods developed to contribute to our understanding of a complex and heterogeneous activity: face-to-face collaborative design and learning. We build on principles of multimodal learning analytics and synthesis research to explore different dimensions of collaboration including the analysis of discourse, tools usage, inscriptions, gestures, physical mobility, focus of attention, decision making, design processes, conversational turns, positioning and other social interactions. We propose that to understand what occurs in a heterogeneous and complex collaboration situation we should see it as a whole: A complex and physically, socially and epistemically situated activity.
Clayphan, A, Martinez-Maldonado, R, Kay, J & Bull, S 2014, 'Scaffolding reflection for collaborative brainstorming', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Tutoring Systems, pp. 615-616.View/Download from: Publisher's site
We present a reflection-on-action system supporting students' reflection and self-assessment after a tabletop brainstorming learning activity. Open Learner Models (OLMs) were core to the reflection task, to scaffold student's self-assessment of egalitarian contribution; and group interaction from ideas sparked from each other. We present multiple OLMs to the group generated from logs automatically captured from the collaborative activity. Our work advances the understanding of OLMs for brainstorm reflection, and the benefit of multiple OLM representations. © 2014 Springer International Publishing Switzerland.
Martinez-Maldonado, R, Clayphan, A, Ackad, C & Kay, J 2014, 'Multi-touch technology in a higher-education classroom: Lessons in-the-wild', Proceedings of the 26th Australian Computer-Human Interaction Conference, OzCHI 2014, 26th Australian Computer-Human Interaction Conference, OzCHI 2014, pp. 220-229.View/Download from: UTS OPUS or Publisher's site
Copyright 2014 ACM. Inspired by the promise of tabletops for collaborative learning, and building on the many tabletop lab studies, and a few in-the-wild tabletop classrooms, we designed the first semester-long use of a multi-tabletop classroom for two university subjects, with 105 and 40 students respectively. Surprisingly, we found that with just three applications, designed to meet emerging teaching goals, we could support diverse classroom activities. Our technology also featured key minimalist functions that proved effective in enhancing the teacher's management of the class. This points to a research agenda for the applications and functionalities needed to make tabletop classrooms a reality. This paper describes the design process we followed to deploy multi-touch technology as a classroom ecology and the lessons learnt from the semester-long use in two authentic university courses.
Martinez-Maldonado, R, Clayphan, A, Yacef, K & Kay, J 2014, 'Towards providing notifications to enhance teacher's awareness in the classroom', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Tutoring Systems, pp. 510-515.View/Download from: UTS OPUS or Publisher's site
Students often need prompt feedback to make the best from the learning activities. Within classrooms, being aware of students' achievements and weaknesses can help teachers decide how to time feedback. However, they usually cannot easily assess student's progress. We present an approach to generate automated notifications that can enhance teacher's awareness in runtime. This paper formulates the theoretical framing and describes the technological infrastructure of a system that can help teachers orchestrate learning activities and monitor small groups in a multi-tabletop classroom. We define the design guidelines underpinning our system, which include: i) generating notifications from teacher-designed or AI-based sources; ii) enhancing teacher's awareness in the orchestration loop; iii) presenting both positive and negative notifications; iv) allowing teachers to tune the system; and v) providing a private teacher's user interface. Our approach aims to guide research on ways to generate notifications that can help teachers drive their attention and provide relevant feedback for small group learning activities in the classroom. © 2014 Springer International Publishing Switzerland.
Martinez-Maldonado, R, Pinto, A & Moreno-Sabido, M 2014, 'Towards a learning ecology using modest computing to address the 'banking model of education'', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Tutoring Systems, pp. 649-651.View/Download from: Publisher's site
It is suggested that most learning technologies used in higher education reinforce what is known as the banking concept of education. Teachers and designers often give too much importance to results and content delivery. We explore the role of learning technologies to promote students' meaningful learning, critical thinking and collaboration, as well as teacher's awareness and orchestration. Our approach aims to bridge the gap between principles of pedagogy, student modelling, modest computing and usability. We will show the applicability of our approach as a learning ecology including in three scenarios: face-to-face, remote, and mobile learning environments. © 2014 Springer International Publishing Switzerland.
Brainstorming is a valuable and widely-used group technique to enhance creativity. Interactive tabletops have the potential to support brainstorming and, by exploiting learners' trace data, they can provide Open Learner Models (OLMs) to support reflection on a brainstorming session. We describe our design of such OLMs to enable an individual to answer core questions: C1) how much did I contribute? C2) at what times was the group or an individual stuck? and C3) where did group members seem to 'spark' off each other? We conducted 24 brainstorming sessions and analysed them to create core brainstorming models underlying the OLMs. We evaluated the OLMs in a think-aloud study designed to see whether learners could interpret the OLMs to answer the core questions. Results indicate the OLMs were effective and that it is valuable, that learners benefit from guidance in their reflection and from drawing on an example of an excellent group's OLM. Our contributions are: i) the first OLMs supporting reflection on brainstorming; ii) models of brainstorming that underlie the OLMs; and iii) a user study demonstrating that learners can use the OLMs to answer the core reflection questions.
Clayphan, A, Martinez-Maldonado, R & Kay, J 2013, 'Open learner models to support reflection on brainstorming at interactive tabletops', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Artificial Intelligence in Education, Springer, Memphis, TN, USA, pp. 683-686.View/Download from: UTS OPUS or Publisher's site
Brainstorming is a widely-used group technique to enhance creativity. Interactive tabletops have the potential to support brainstorming and, by exploiting learners' trace data, they can provide Open Learner Models (OLMs) to support reflection on a brainstorming session. We describe our design of such OLMs to enable an individual to answer core questions: C1) how much did I contribute? C2) at what times was the group or an individual stuck? and C3) where did group members seem to 'spark' off each other? We conducted 24 brainstorming sessions and analysed them to create brainstorming models underlying the OLMs. Results indicate the OLM's were effective. Our contributions are: i) the first OLMs supporting reflection on brainstorming; ii) models of brainstorming that underlie the OLMs; and iii) a user study demonstrating that learners can use the OLMs to answer core reflection questions. © 2013 Springer-Verlag Berlin Heidelberg.
Clayphan, A, Martinez-Maldonado, R, Ackad, C & Kay, J 2013, 'An approach for designing and evaluating a plug-in vision-based tabletop touch identification system', Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, OzCHI 2013, Australian Computer Human Interaction Conference, ACM, Adelaide, Australia, pp. 373-382.View/Download from: UTS OPUS or Publisher's site
Key functionality for interactive tabletops to provide effective collaboration affordances requires touch identification, where each touch is matched to the right user. This can be valuable to provide adaptive functions, personalisation of content, collaborative gestures and capture of differentiated interaction for real-time or further analysis. While there is increased attention on touch-identification mechanisms, currently there is no developed solution to readily enhance available tabletop hardware to include such functionality. This paper proposes a plug-in system that adds touch identification to a conventional tabletop. It also presents an analysis tool and the design of an evaluation suite to inform application designers of the effectiveness of the system to differentiate users. We illustrate its use by evaluating the solution under a number of conditions of: scalability (number of users); activity density; and multi-touch gestures. Our contributions are: (1) an offthe- shelf system to add user differentiation and tracking to currently available interactive tabletop hardware; and (2) the foundations for systematic assessment of touch identification accuracy for vision-based systems.
Kharrufa, A, Martinez-Maldonado, R, Kay, J & Olivier, P 2013, 'Extending tabletop application design to the classroom', ITS 2013 - Proceedings of the 2013 ACM International Conference on Interactive Tabletops and Surfaces, ACM Interactive Tabletops and Surfaces Conference, ACM, Scotland, United Kingdom, pp. 115-124.View/Download from: UTS OPUS or Publisher's site
While a number of guidelines exist for the design of learning applications that target a single group working around an interactive tabletop, the same cannot be said for the design of applications intended for use in multi-tabletops deployments in the classroom. Accordingly, a number of these guidelines for single-tabletop settings need to be extended to take account of both the distinctive qualities of the classroom and the particular challenges of having various groups using the same application on multiple tables simultaneously. This paper presents an empirical analysis of the effectiveness of designs for small-group multi-tabletop collaborative learning activities in the wild. We use distributed cognition as a framework to analyze the small number of authentic multi-tabletop deployments and help characterize the technological and educational ecology of these classroom settings. Based on previous research on single-tabletop collaboration, the concept of orchestration, and both first-hand experience and second-hand accounts of the few existing multiple-tabletop deployments to date, we develop a three-dimensional framework of design recommendations for multi-tabletop learning settings. © 2013 ACM.
Martinez-Maldonado, R, Dimitriadis, Y, Clayphan, A, Muñoz-Cristóbal, JA, Prieto, LP, Rodríguez-Triana, MJ & Kay, J 2013, 'Integrating orchestration of ubiquitous and pervasive learning environments', Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, OzCHI 2013, Australian Computer Human Interaction Conference, ACM, Adelaide, Australia, pp. 189-192.View/Download from: UTS OPUS or Publisher's site
Ubiquitous and pervasive computing devices, such as interactive tabletops, whiteboards, tablets and phones, have the potential to enhance the management and awareness of learning activities in important ways. They provide students with natural ways to interact with collaborators, and can help teachers create and manage learning tasks that can be carried out both in the classroom and at a distance. But how can these emerging technologies be successfully integrated into current teaching practice? This paper proposes an approach to integrate, from the technological perspective, collaborative learning activities using these kinds of devices. Our approach is based on the concept of orchestration, which tackles the critical task for teachers to coordinate student's learning activities within the constraints of authentic educational settings. Our studies within authentic learning settings enabled us to identify three main elements that are important for ubiquitous and pervasive learning settings. These are i) regulation mechanisms, ii) interconnection with existing web-based learning environments, and iii) awareness tools.
Martinez-Maldonado, R, Kay, J & Yacef, K 2013, 'An automatic approach for mining patterns of collaboration around an interactive tabletop', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Artificial Intelligence in Education, Springer, Memphis, TN, USA, pp. 101-110.View/Download from: UTS OPUS or Publisher's site
Learning to collaborate is important. But how does one learn to collaborate face-to-face? What are the actions and strategies to follow for a group of students who start a task? We analyse aspects of students' collaboration when working around a multi-touch tabletop enriched with sensors for identifying users, their actions and their verbal interactions. We provide a technological infrastructure to help understand how highly collaborative groups work compared to less collaborative ones. The contributions of this paper are (1) an automatic approach to distinguish, discover and distil salient common patterns of interaction within groups, by mining the logs of students' tabletop touches and detected speech; and (2) the instantiation of this approach in a particular study. We use three data mining techniques: a classification model, sequence mining, and hierarchical clustering. We validated our approach in a study of 20 triads building solutions to a posed question at an interactive tabletop. We demonstrate that our approach can be used to discover patterns that may be associated with strategies that differentiate high and low collaboration groups. © 2013 Springer-Verlag Berlin Heidelberg.
Martinez-Maldonado, R, Kay, J, Yacef, K, Edbauer, MT & Dimitriadis, Y 2013, 'MTClassroom and MTDashboard: Supporting analysis of teacher attention in an orchestrated multi-tabletop classroom', Computer-Supported Collaborative Learning Conference, CSCL, pp. 320-327.
In spite of the substantial progress in CSCL, there is still some distance between the promise of educational technology for classroom learning and what is readily achieved. Emerging tabletop devices can offer new means to enhance teachers' classroom control and awareness. These technologies can help them orchestrate activities, and capture, analyse and visualise students' collaborative interactions. This paper presents MTClassroom and MTDashboard, that were designed, deployed and tested to support the teacher in orchestrating collaborative learning activities at an authentic classroom. MTClassroom is an enriched multi-tabletop environment that captures aspects of students' activity as they work in small groups. MTDashboard is an orchestration tool displayed at a handheld device, giving the teacher control over classroom activities and providing 'real-time' indicators of participation and task progress of each group. We analysed teacher's attention by triangulating quantitative evidence captured by our environment with qualitative observations and teacher's perceptions. We investigated the affordances of our environment and the impact of the information provided to the teacher through the MTDashboard. The contribution of this paper is the novel approach for providing teachers with key indicators of small-group collaboration in the classroom and analysing their impact on teachers' attention to help them manage their time more effectively. © ISLS.
Rick, J, Horn, M & Martinez-Maldonado, R 2013, 'Human-computer interaction and the learning sciences', Computer-Supported Collaborative Learning Conference, CSCL, pp. 451-455.
Human-Computer Interaction (HCI) research has been highly influential in understanding the potential of new technologies to support human activities. Research in the Learning Sciences (LS) draws on multiple fields to improve learning and education. Both are active research communities with well-established practices, core values and a substantial body of literature. As both concentrate on utilizing computing technologies to better support people, there is a natural overlap; however, the Learning Sciences are not simply HCI applied to the domain of learning. The practices, traditions, and values are substantially different leading to tensions are keenly felt by researchers who actively participate in both fields. They also make it harder for researchers in either field to move towards the other. To explore and improve the relationship between these fields, we organized the workshop "Human-Computer Interaction and the Learning Sciences." This workshop was meant for both interdisciplinary researchers (i.e., active participants in both communities) and researchers from either discipline interested in the other field. In this paper, we support these audiences by providing introductions to the two fields: their histories, values and practices. © ISLS.
Evans, MA, Rick, J, Horn, M, Shen, C, Mercier, E, McNaughton, J, Higgins, S, Burd, E, Tissenbaum, M, Lui, M, Slotta, JD, Maldonado, RM & Clayphan, A 2012, 'Interactive surfaces and spaces: A learning sciences agenda', 10th International Conference of the Learning Sciences: The Future of Learning, ICLS 2012 - Proceedings, pp. 78-85.
Interactive surfaces and spaces are entering classrooms and other learning settings. This symposium brings together leaders in the field to establish a coherent research agenda for interactive surfaces inside the learning sciences. We demonstrate the broad applicability of these technologies, outline advantages and disadvantages, present relevant analytical frameworks, and suggest themes to guide future research and application. © ISLS.
Maldonado, RM, Kay, J, Yacef, K & Schwendimann, B 2012, 'Unpacking traces of collaboration from multimodal data of collaborative concept mapping at a tabletop', 10th International Conference of the Learning Sciences: The Future of Learning, ICLS 2012 - Proceedings, pp. 241-245.
During collaborative student work, teachers aim to support groups effectively and ensure that each group member can contribute at some level. Analysing the final product of group work does not reveal individual contributions or the collaborative process. This research investigates indicators of collaborative learning, captured by a novel tabletop environment, which can provide real-time information about the ongoing collaborative work. This can enable teachers to direct their attention more effectively. This paper reports findings from a case study on collaborative concept mapping. Five triads of university students engaged in a collaborative activity on the topic of human nutrition. The variables, level of participation, symmetry of participation, similarity of previous knowledge, knowledge contribution, transactivity, interaction and knowledge creation, were used to describe the collaborative process. Results offer promise for transforming this collaboration data to give informative feedback to teachers and support collaborative learning. © ISLS.
Martinez Maldonado, R, Kay, J, Yacef, K & Schwendimann, B 2012, 'An interactive teacher's dashboard for monitoring groups in a multi-tabletop learning environment', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Intelligent Tutoring Systems, Springer, Chania, Crete, Greece, pp. 482-492.View/Download from: UTS OPUS or Publisher's site
One of the main challenges for teachers in facilitating and orchestrating collaborative activities within multiple groups is that they cannot see information in real time and typically see only the final product of the groups' activity. This is a problem as it means that teachers may find it hard to be aware of the learners' collaborative processes, partial solutions and the contribution of each student. Emerging shared devices have the potential to provide new forms of support for face-to-face collaboration and also open new opportunities for capturing and analysing the collaborative process. This can enable teachers to monitor students' learning more effectively. This paper presents an interactive dashboard that summarises student data captured from a multi-tabletop learning environment and allows teachers to drill down to more specific information when required. It consists of a set of visual real-time indicators of the groups' activity and collaboration. This study evaluates how teachers used the dashboard determine when to intervene in a group. The key contributions of the paper are the implementation and evaluation of the dashboard, which shows a form of learner model from a concept mapping tabletop application designed to both support collaborative learning and capture traces of activity. © 2012 Springer-Verlag.
Martinez Maldonado, R, Kay, J, Yacef, K, Edbauer, MT & Dimitriadis, Y 2012, 'Orchestrating a multi-tabletop classroom: From activity design to enactment and reflection', ITS 2012 - Proceedings of the ACM Conference on Interactive Tabletops and Surfaces, ACM Interactive Tabletops and Surfaces Conference, ACM, Cambridge, Massachusetts, USA, pp. 119-128.View/Download from: UTS OPUS or Publisher's site
If multi-tabletop classrooms were available in each school, how would teachers plan and enact their activities to enhance learning and collaboration? How can they evaluate how the activities actually went compared with the plan? Teachers' effectiveness in orchestrating the classroom has a direct impact on students learning. Interactive tabletops offer the potential to support teachers by enhancing their awareness and classroom control. This paper describes our mechanisms to help a teacher orchestrate a classroom activity using multiple interactive tabletops. We analyse automatically captured interaction data to assess whether the activity design, as intended by the teacher, was actually followed during its enactment. We report on an authentic classroom study embedded in the curricula of an undergraduate Management unit. This involved 236 students across 14 sessions. The main contribution of the paper is an approach for designing a multi-tabletop classroom that can help teachers plan their learning activities; and provide data for assessment and reflection on the enactment of a series of classroom sessions. © 2012 ACM.
Martinez, R, Slotta, J, Dillenbourg, P, Clayphan, A, Tissenbaum, M, Schwendimann, B & Ackad, C 2012, 'Digital ecosystems for collaborative learning: Embedding personal and collaborative devices to support classrooms of the future', 10th International Conference of the Learning Sciences: The Future of Learning, ICLS 2012 - Proceedings, pp. 588-589.
Multi-touch tables, interactive whiteboards, motion sensitive interfaces, physical and tangible computers, all present enticing new functional affordances for learning. However, this constitutes a problem space for design, rather than any specific solution. What forms of learning can now be supported by a multi-user touch screen? How can such learning be incorporated into K-12, university, or informal learning designs? As new commercial offerings become available, it is timely for learning scientists and educators to explore how to best make use of these tools at the classroom. This workshop will offer a venue to discuss how to develop novel technology into supportive tools and intelligent mediators between peers' activity to build the classroom of the future. We will discuss the role of technology and its limitations along with the roles of teachers and students. This workshop gives participants the opportunity to experience such a classroom, share their work, discuss practical challenges and define an agenda for future work. © ISLS.
Martinez, R, Ackad, C, Kay, J & Yacef, K 2011, 'Designing tabletop-based systems for user modelling of collaboration', CEUR Workshop Proceedings, pp. 47-51.
Tabletops offer a new form of interaction and create new possibilities for small groups of people to collaborate and discuss tasks aided by the shared use of digital materials and tools. The collaborative affordances of tabletops make them suitable for many uses in public spaces as well as in more restricted environments such as workplaces and learning settings. This creates new opportunities for improving collaboration, particularly by capturing data that can be used to model the nature of the interactions and to present this model to the users in a form that will facilitate improved collaboration. It is timely to establish principles for designing tabletop-based systems in a manner that can facilitate such modelling. These principles should support effective use of data mining tools to create group collaboration models. In this paper, we outline theoretical design principles based on a careful analysis of the nature of tabletop datasets and collaboration.
Martínez, R, Collins, A, Kay, J & Yacef, K 2011, 'Who did what? Who said that? Collaid: An environment for capturing traces of collaborative learning at the tabletop', Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces, ITS'11, pp. 172-181.View/Download from: Publisher's site
Tabletops have the potential to provide new ways to support collaborative learning generally and, more specifically, to aid people in learning to collaborate more effectively. To achieve this potential, we need to gain understanding of how to design tabletop environments so that they capture relevant information about collaboration processes so that we can make it available in a form that is useful for learners, their teachers and facilitators. This paper draws upon research in computer supported collaborative learning to establish a set of principles for the design of a tabletop learning system. We then show how these have been used to design our Collaid (Collaborative Learning Aid) environment. Key features of this system are: capture of multi-modal data about collaboration in a tabletop activity using a microphone array and a depth sensor; integration of these data with other parts of the learning system; transforming the data into visualisations depicting the processes that occurred during the collaboration at the table; and sequence mining of the interaction logs. The main contributions of this paper are: our design guidelines to build the Collaid environment and the demonstration of its use in a collaborative concept mapping learning tool applying data mining and visualisations of collaboration. © 2011 ACM.
Martinez, R, Kay, J & Yacef, K 2011, 'Visualisations for longitudinal participation, contribution and progress of a collaborative task at the tabletop', Connecting Computer-Supported Collaborative Learning to Policy and Practice: CSCL 2011 Conference Proceedings - Long Papers, 9th International Computer-Supported Collaborative Learning Conference, pp. 25-32.
One of the challenges for facilitators in collaborative work is that they typically see only the final product of a groups' interactive work. This is a problem as it means that the role of each individual may be hard to determine. This paper proposes a set of visualisations which aim to give teachers insights into longitudinal participation of each group member, an indication of the extent of each learner's contribution and the building process of the group product in terms of overall activity towards a good solution. We exploit the affordances of tabletops to capture the data in order to infer these visualisations. We evaluate these by assessing whether facilitators could answer key questions about aspects of groups. Key contributions of the paper are the design of new visualisations, results of their evaluation and the implementation of a tabletop concept mapping application which was carefully designed to both support collaboration and capture of the history of the collaborative process. © ISLS.
Martinez, R, Kay, J, Wallace, JR & Yacef, K 2011, 'Modelling symmetry of activity as an indicator of collocated group collaboration', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 207-218.View/Download from: Publisher's site
There are many contexts where it would be helpful to model the collaboration of a group. In learning settings, this is important for classroom teachers and for students learning collaboration skills. Our approach exploits the digital and audio footprints of the users' actions at collocated settings to automatically build a model of symmetry of activity. This paper describes our theoretical model of collaborative learning and how we implemented it. We use the Gini coefficient as a statistical indicator of symmetry of activity, which is itself an important indicator of collaboration. We built this model from a small-scale qualitative study based on concept mapping at an interactive tabletop. We then evaluated the model using a larger scale study based on a corpus of coded data from a multi-display groupware collocated setting. Our key contributions are the model of symmetry of activity as a foundation for modelling collaboration within groups that should have egalitarian participation, the operationalisation of the model and validation of the approach on both a small-scale qualitative study and a larger scale quantitative corpus of data. © 2011 Springer-Verlag.
Martinez, R, Wallace, JR, Kay, J & Yacef, K 2011, 'Modelling and identifying collaborative situations in a collocated multi-display groupware setting', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 196-204.View/Download from: Publisher's site
Detecting the presence or absence of collaboration during group work is important for providing help and feedback during sessions. We propose an approach which automatically distinguishes between the times when a co-located group of learners, using a problem solving computer-based environment, is engaged in collaborative, non-collaborative or somewhat collaborative behaviour. We exploit the available data, audio and application log traces, to automatically infer useful aspects of the group collaboration and propose a set of features to code them. We then use a set of classifiers and evaluate whether their results accurately match the observations made on video-recordings. Results show up to 69.4% accuracy (depending on the classifier) and that the error rate for extreme misclassification (e.g. when a collaborative episode is classified as non-collaborative, or vice-versa) is less than 7.6%. We argue that this technique can be used to show the teacher and the learners an overview of the extent of their collaboration so they can become aware of it. © 2011 Springer-Verlag Berlin Heidelberg.
Martinez, R, Yacef, K, Kay, J, Al-Qaraghuli, A & Kharrufa, A 2011, 'Analysing frequent sequential patterns of collaborative learning activity around an interactive tabletop', EDM 2011 - Proceedings of the 4th International Conference on Educational Data Mining, pp. 111-120.
Electronic traces of activity have the potential to be an invaluable source to understand the strategies followed by groups of learners working collaboratively around a tabletop. However, in tabletop and other co-located learning settings, high amounts of unconstrained actions can be performed by different students simultaneously. This paper introduces a data mining approach that exploits the log traces of a problem-solving tabletop application to extract patterns of activity in order to shed light on the strategies followed by groups of learners. The objective of the data mining task is to discover which frequent sequences of actions differentiate high achieving from low achieving groups. An important challenge is to interpret the raw log traces, taking the user identification into account, and pre-process this data to make it suitable for mining and discovering meaningful patterns of interaction. We explore two methods for mining sequential patterns. We compare these two methods by evaluating the information that they each discover about the strategies followed by the high and low achieving groups. Our key contributions include the design of an approach to find frequent sequential patterns from multiuser co-located settings, the evaluation of the two methods, and the analysis of the results obtained from the sequential pattern mining.
Maldonado, RM, Kay, J & Yacef, K 2010, 'Collaborative concept mapping at the tabletop', ACM International Conference on Interactive Tabletops and Surfaces, ITS 2010, pp. 207-210.View/Download from: Publisher's site
Concept mapping is a technique where users externalise their conceptual and propositional knowledge of a domain in a way that can be readily understood by others. It is widely used in education, so that a learner's understanding is made available to their peers and to teachers. There is considerable potential educational benefit in collaborative concept mapping, and the tabletop is an ideal tool for this. This paper describes Cmate, a tabletop collaborative concept mapping system. We describe its design process and how this draws upon both the principles of concept mapping and on those for creating educational applications on tabletops. © 2010 ACM.