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The document discusses the role of teachers as designers and orchestrators of technology-enhanced collaborative learning, highlighting the importance of collaboration in education. It examines the challenges and solutions related to designing effective collaborative learning environments, considering various tools, patterns, and management strategies. The document emphasizes the need for human-centered approaches and support systems to enhance teachers' capabilities in fostering collaborative learning in both virtual and real-world contexts.

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Teachers as designers and orchestrators of technology- enhanced collaborative learning: Challenges and solutions Prof. Yannis Dimitriadis GSIC/EMIC group University of Valladolid, Spain CollabTech2022 10 November 2022
Why collaboration matters (I) n Collaboration as a philosophical and political value – Value to consider in human-centered value-sensitive design n Collaboration as a learning/education mechanism – Mechanism to be understood, activated and optimized n Collaboration as a design target – Product and process to be designed for learning by teachers n Collaboration as a construct/concept – Construct to be estimated in Socially Shared Regulated Learning (SSRL) and co-RL n Collaboration as a social mechanism – Mechanism to be orchestrated in real-world classrooms 2
Why collaboration matters (II) n Collaboration as a philosophical and political value – Value to consider in human-centered value-sensitive design – How can we design considering ethical/political values regarding the involved stakeholders? n Collaboration as a learning/education mechanism – Mechanism to be understood, activated and optimized – Is collaborative learning effective or how can it be more effective? n Collaboration as a design target – Product and process to be designed for learning by teachers – How can teachers (and other instructional designers) design for learning? 3
Why collaboration matters (III) n Collaboration as a construct/concept – Construct to be estimated in Socially Shared Regulated Learning (SSRL) and co-RL – How can we measure theoretical concepts so that pedagogical interventions can be made? n Collaboration as a social mechanism – Mechanism to be orchestrated in real-world classrooms – What are the ways that teachers can put collaboration in practice and manage it in real-world contexts? 4
A view of the TEL/CSCL ecosystem How to design for learning in it? 5
Support teachers for collaboration A contemporary technology-enhanced learning (TEL) ecosystem is complex, and collaboration is complex to achieve What are the conceptual and technological tools to support teachers as designers and orchestrators for Computer Supported Collaborative Learning (CSCL)? 6
What is this talk about (I) n How to design for effective and efficient (computer supported) collaborative learning? n How teachers as designers and orchestrators may be supported? – What are the main challenges and solutions regarding conceptual and technological support tools? n building on and adapting to existing design knowledge …. n Overview of patterns, approaches, tools, and systems that should respect teachers’ agency 7
What is this talk about (II) n Take advantage of complex computational approaches, typically based on artificial intelligence n Special attention to recent research on – How learning analytics solutions may be designed and implemented using human-centered approaches? – How socially shared regulated learning (SSRL) and co- regulation may be better supported? n Illustrating examples from the last 25 years n Prominent issues to guide future research 8
Contents (I) n Some fundamental questions – Is (CS)CL effective in terms of learning outcomes? – Are there any (successful) patterns/scripts for (CS)CL? – What and how to design for (collaborative) learning? – How can teachers design and orchestrate for (CS)CL? n How to manage technology in CSCL contexts? – Collaboration management cycle – Technology for Collaboration – Distributed Scaffolding in complex CSCL ecosystems – Learning Analytics and AI for CSCL – From data to collaboration analytics – Human-Centered and Value-Sensitive Design 9
Contents (II) n Examples of models, tools, architectures, applications – Learning Design authoring and deployment tools – Dialogic Feedback: Framework and system – Detection and support of SSRL – Group Formation in MOOCs – Prediction and interventions in MOOCs – Detection of participatory roles n Challenges and future directions n Take home messages 10
Is (CS)CL effective? n Meta-analytical evidence (Kollar et al., in prep) shows that CSCL is an effective way to foster learning, with moderate effect sizes on learning outcomes – Part of these effects can be attributed to the provision of computer support – Scaffold collaboration increases the effects of CSCL even more, for example through the provision of CSCL scripts – All these effects, however, seem to be moderated by distal variables such as the participants’ educational level, the domain of study, or the intervention duration n More meta-studies necessary for effects on learning processes, qualitative studies, technical papers 11 Kollar, I., Greisel, M., Özbek, T., Spang, L. & Vogel, F. (in prep.). Computer-supported collaborative learning. To be included in A. Gegenfurtner & I. Kollar (Eds.), Designing effective digital learning environments. Routledge.
Patterns/scripts for (CS)CL? n Effective and efficient (CS)CL unlikely to occur – External obstacles (curriculum, competencies, cost, practical issues) – Psychological, social and technological issues (group formation and roles, need for collaboration, technology complexity, mindsets) n Pedagogical patterns/scripts to increase the chances for success n Support to design for successful (CS)CL 12
(CS)CL (design) patterns Think-Pair-Share Think-Pair-Share (TPS) pattern – It structures collaboration and promotes participation in large classes They comment or take a classroom “vote” They pair and discuss their ideas about the question Each participant has time to think about the question 13
(CS)CL (design) patterns Jigsaw/Puzzle Individual or initial group Teacher Introductory individual (or initial group) activity Collaborative activity around the sub-problem Collaborative activity around the problem and solution proposal Jigsaw pattern – It allows for individual accountability and positive interdependence
(CS)CL Flow/assessment patterns 15 n Learning Flow n Assessment
Aligning both sets of patterns 16
Usefulness of patterns 17 n Are these patterns useful for practitioners? n Evidence for learning flow patterns for OER repurposing to collaborative activities n Appropriation in Higher Education teachers (Professional Development workshops) n But not always n If not included in appropriate technological tools n Too abstract for Primary Education practitioners n Do not consider enactment issues
The need for atomic patterns 18 n Two independent studies by GSIC and SRI using Group Scribbles in schools n Studying enactment and disciplined improvisation n Showed that other small-scale, informal, contextual, actionable patterns emerged
A learning design in action Orchestration graphs 19
Use of pedagogical/design pattterns 20 What for? 1. Understand, compile and represent design knowledge (principles, patterns, procedures) 2. Empower and support teachers as designers (professional development) 3. Inform and embed design in tools and architectures (systems perspective)
An orchestration framework 21 L.P. Prieto, Y. Dimitriadis, J.I. Asensio, C-K. Looi, “Orchestration in Learning Technology Research: Evaluation of a Conceptual Framework”, Research in Learning Technology (2015), 23: 28019 - http://dx.doi.org/10.3402/rlt.v23.28019 .
Learning Design (LD) or Design for Learning (D4L) - I n Learning is the objective of education – Can we (pedagogically) inform and (technologically) support teachers (and other stakeholders) in creating effective (and efficient?) learning situations n Main metaphor: – “Teachers as designers” n Main issue: – Is it possible that teachers (and other stakeholders) work as other traditional designers (e.g., architects, engineers)? – Can design form part of the normal flow of educational activities? 22
Design for Learning – II “In media res framework” n What can be designed for learning? – The learning (performed by students) and support (made by teachers) tasks n The “physical” environment n Spaces, tools, infrastructures, artifacts-resources (to be consumed and/or produced) n The social architecture n Groupings, interactions with external agents n Design is indirect (tasks vs. activities) n Learners may change-interpret tasks in learntime 23 P. Goodyear, Y. Dimitriadis, “In medias res: reframing design for learning”, Research in Learning Technology, Research in Learning Technology Supplement (2013); 21: 19909 - http://dx.doi.org/10.3402/rlt.v21i0.19909 .
Design for Learning – III “Activity-Centered Analysis and Design” (ACAD) 24 Goodyear, P., Carvalho, L. & Yeoman, P. Activity-Centred Analysis and Design (ACAD): Core purposes, distinctive qualities and current developments. Education Tech Research Dev 69, 445–464 (2021). https://doi.org/10.1007/s11423-020-09926-7
Design for Learning Some notes on the framework 25 n In the new real contexts n Teachers cannot resolve all emerging problems n There are many internal and external conditions n An equilibrium should be found between n Learners’ autonomy (“agency”) n Structuring and guiding (“structure, scripting”) n The process of D4L is nontrivial n Meet several objectives that are eventually contradictory
Design for Learning (D4L) Some notes on the framework 26 n Who is going to control the learning process? n The teacher / designer n The student / learner n The devices / resources / virtual agents of the learning environment n D4L should look forward (forward-oriented design) in order to support the different phases n Configuration, orchestration, reflection, redesign ...
Forward oriented design - I 27 n Design for Configuration: n Prepare, particularize, or modify what had been designed beforehand n Adapt to specific requirements of the context n Design for Orchestration n Support teachers (and students) at learn time Y. Dimitriadis, P. Goodyear, “Forward-oriented design for learning: Illustrating the approach”, Research in Learning Technology Supplement (2013), 21: 20290 - http://dx.doi.org/10.3402/rlt.v21i0.20290
Forward oriented design - II n Design for Reflection n Be sure that monitoring can take place n Offer “awareness” at learn time n Allow for regulation and scaffolding n Inform evaluation of the intervention and assessment of learning n Design for Redesign n Take design decisions so that posterior modifications of the design can be made easily
TinkerLamp Design for orchestration 29 Do-Lenh, S., Jermann, P., Legge, A., Zufferey, G., Dillenbourg, P. (2012). TinkerLamp 2.0: Designing and Evaluating Orchestration Technologies for the Classroom. In: Ravenscroft, A., Lindstaedt, S., Kloos, C.D., Hernández-Leo, D. (eds) 21st Century Learning for 21st Century Skills. EC-TEL 2012. Lecture Notes in Computer Science, vol 7563. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33263-0_6
GroupScribbles Design for social coordination 30
Spaces for collaboration Design physical (and digital) environment 31
Group concept maps Full set of forward-oriented design 32 R. Martínez, Y. Dimitriadis, A. Martínez, J. Kay, K. Yacef “Capturing and analysing verbal and physical collaborative learning interactions at an enriched interactive tabletop”, International Journal of Computer Supported Collaborative Learning, 8(4), 455-485 (2013)
Teaching as a design science n “In media res”: Design forms part of the “normal flow” of educational activities n Teaching as a design science n Teaching is not only an art. It has a formally defined goal n It builds on design principles, rather than theories, and heuristics of practice than explanations n See also Design Based Research, co-design, … n Design patterns externalize knowledge and allow for discussion and sharing … Laurillard, D. (2018). Teaching as a Design Science: Teachers Building, Testing, and Sharing Pedagogic Ideas. In: Voogt, J., Knezek, G., Christensen, R., Lai, KW. (eds) Second Handbook of Information Technology in Primary and Secondary Education . Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-319-71054-9_108
Supporting the D4L lifecycle Objectives, Activities … Students, resources, ICT tools… How to Enhance? Design for Learning lifecycle
• Conceptualize • Author • Implement • Share • Evaluate • Explore Integrated Learning Design Environment http://ilde2.upf.edu The METIS ILDE The ILDE environment
Example at UVA: “Landscape organization” (Geography)
And the course in Moodle!
n ILDE – It fits the needs of several educational contexts – It is independent from the pedagogical approach adopted – It covers all the phases of the LD lifecycle – It is usable by the ‘average’ teacher n Pedagogy is the “king” n Support is needed for enactment and communities beyond workshops Some METIS findings Some findings on ILDE J. I. Asensio, Y. Dimitriadis, F. Pozzi, D. Hernández, L.P. Prieto, D. Persico, S. Villagrá, “Towards Teaching as Design: exploring the interplay between full lifecycle Learning Design tooling and Teacher Professional Development”. Computers & Education, 114, 92-116 (2017).
n First Order Barriers – Lack of institutional support – Lack of adequate teacher training – Time/workload factors – Conceptual complexity of method and tools – Adoption by peers n Second order barriers – Use of ICTs in teaching practice – Teachers’ motivation Some METIS findings Barriers for adoption of LD F. M. Dagnino, Y. Dimitriadis, F. Pozzi, J.I. Asensio-Pérez, B. Rubia-Avi, “Exploring teachers’ needs and the existing barriers to the adoption of Learning Design methods and tools: a literature survey”, British Journal of Educational Technology, 49(6) 998-1013 (2018)
Some METIS findings Lightweight tools for CSCL patterns The PyramidApp D. Manathunga, K., Hernández-Leo (2018), Authoring and enactment of mobile pyramid based collaborative learning activities, British Journal of Educational Technology, 49(2),262–275, doi:10.1111/bjet.12588
Collaboration tools/resources n Building the foundation or context for collaboration n Building interventions within contexts n Orchestrating student and teacher activities n Analyzing data 41 Rosé, C., Dimitriadis, Y. (2021). Tools and Resources for Setting Up Collaborative Spaces. In: Cress, U., Rosé, C., Wise, A.F., Oshima, J. (eds) International Handbook of Computer-Supported Collaborative Learning. Computer-Supported Collaborative Learning Series, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-030-65291-3_24.
The collaboration management cycle 42 Soller, A., Martínez-Monés, A., Jermann, P., Muehlenbrock, M. (2005) From Mirroring to Guiding: A Review of the State of the Art Technology for Supporting Collaborative Learning International Journal of Artificial Intelligence in Education (ijAIED). 15:261-290
Distributed scaffolding 43 • Puntambekar, S. Distributed Scaffolding: Scaffolding Students in Classroom Environments. Educ Psychol Rev (2021). https://doi.org/10.1007/s10648-021-09636-3 • https://www.imec-int.com/en/research-portfolio/steams: Supporting TEAMS in ambient learning spaces Across 1. Tools and social scaffolds 2. Levels (individual, group, and whole class) 3. Time and Contexts
Collaboration analytics (I) n Collaboration Analytics – Collocated, face-to-face groups, and platform-mediated groups (synchronous and asynchronous) – Help the team, educators, researchers or other stakeholders gain insights into the activity, and inform action that improves collaboration processes and products n Collaboration analytics require the integration of – (i) theoretically sound concepts – (ii) well designed tasks that generate useful data traces to inform analytics – (iii) human-centered design that empowers stakeholders to shape the analytics and produces effective user interfaces 44 Martinez-Maldonado, R., Gašević, D., Echeverria, V., Fernandez Nieto, G., Swiecki, Z., & Buckingham Shum, S. (2021). What Do You Mean by Collaboration Analytics? A Conceptual Model. Journal of Learning Analytics, 8(1), 126-153. https://doi.org/10.18608/jla.2021.7227.
Collaboration analytics (II) 45 Martinez-Maldonado, R., Gašević, D., Echeverria, V., Fernandez Nieto, G., Swiecki, Z., & Buckingham Shum, S. (2021). What Do You Mean by Collaboration Analytics? A Conceptual Model. Journal of Learning Analytics, 8(1), 126-153. https://doi.org/10.18608/jla.2021.7227.
Human-Centered Learning Analytics 46 Human-Centered Design should involve: Inclusion via stakeholder participation in the design process + Empathic experiences (particularly when making design decisions) Giacomin, J. (2014). What is human centred design? The Design Journal, 17(4), 606–623. https://doi.org/10.2752/175630614X140561854801.
Levels of human-centeredness 47 Smuha N.A. (2023). “Pitfalls and pathways for trustworthy Artificial Intelligence in education” in The Ethics of Artificial Intelligence in Education Practices, Challenges, and Debates, W. Holmes, K. Porayska-Pomsta (Eds). Taylor and Francis. n Human in command – Oversee when and how to use AI/ITS n Human on the loop – Participate in design and operation n Human in the loop – Get involved in every lifecycle phase
Human-Centeredness in MMLA-AIED 48 Kukurova, M. (2022). “Multimodal Learning Analytics in Real-world Practice: A Bridge Too Far?”, Webinar at Spanish Network of Learning Analytics (SNOLA), May 2022. https://snola.es/2022/05/03/webinar-multimodal-learning- analytics-in-real-world-practice-a-bridge-too-far-mutlu-cukurova/
Human-centered and trustworthy AI 49 • Delgado Kloos, C., et al. (2022), H2O Learn - Hybrid and Human-Oriented Learning: Trustworthy and Human- Centered Learning Analytics (TaHCLA) for Hybrid Education. IEEE Global Engineering Education Conference, EDUCON 2022, • HLEG-AI (High-Level Expert Group on Artificial Intelligence) (2019), “Ethics Guidelines for Trustworthy AI: Requirements of Trustworthy AI,” Available: https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines/1
Orchestration and LA (OrLA) 50
LA-based orchestration tools for CSCL Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance 51 n Orchestration tools build upon learning analytics n Information that could be adapted to the specific situation n Detrimental effects if not tailored to a teacher’s needs n Teachers in the advising condition more often detected the problematic group, needed less effort to do so, and were more confident of their decisions Anouschka van Leeuwen, Nikol Rummel. 2020. Comparing Teachers’ Us of Mirroring and Advising Dashboards. In Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK’20). ACM, New York, NY, USA, X pages.
Collaborative Dialogic Feedback (I) Framework 52 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): A collaborative learning approach to dialogic peer feedback: a theoretical framework, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1786497
Dialogic Feedback (II) Design principles n Connect self-evaluation with peer evaluations n Provide opportunities to resolve the discrepancies in students’ perspectives about the quality of the work n Provide mechanisms to (collectively) plan the feedback before its provision n Enable dialogue around the feedback to support its uptake n Enable students to set goals and create an action plan with peers based on the feedback n Enable dialogue with peers while students are revising their work 53 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): A collaborative learning approach to dialogic peer feedback: a theoretical framework, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1786497
Dialogic feedback (III) The Synergy system 54 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): Collaborative peer feedback and learning analytics: theory-oriented design for supporting class-wide interventions, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1764490
Socially Shared Regulated Learning (I) 55 Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance Socially-Shared Regulation of Learning Cognitive Metacognitive Motivation Emotions
Socially Shared Regulated Learning (II) To extract meaningful SSRL indicators from trace data to support groups during collaboration Cristina Villa-Torrano How have we incorporated SSRL phases in the design? Task Understanding Setting Goals & Planning, Adaptation Task Enactment 56
Socially Shared Regulated Learning (III) Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance Which data sources do we have to extract meaningful information? 57
Detection/adaptation of roles 58 J.A. Marcos, A. Martínez, Y. Dimitriadis, “DESPRO: A method based on roles to provide collaboration analysis support adapted to the participants in CSCL situations”, Computers & Education, 82 235-253 (2015)
Group Formation in MOOCs n Support for CSCL in MOOCs (guide and tool) n Design guide allowed teachers – Be aware of the contextual factors to consider when forming the collaborative groups – Be informed about some configuration parameters of the activity and the group formation n Strategy with higher degree of homogeneity – Grouped students with similar levels of engagement – Achieved best results in terms of group performance, group interactions and student satisfaction 59 Luisa Sanz-Martínez, Erkan Er, Alejandra Martínez-Monés, Yannis Dimitriadis & Miguel L. Bote-Lorenzo (2019) Creating collaborative groups in a MOOC: a homogeneous engagement grouping approach, Behaviour & Information Technology, 38:11, 1107-1121, DOI: 10.1080/0144929X.2019.1571109
Prediction/interventions in MOOCs n Predictive models – Accurately classify learners according to their expected engagement levels in an upcoming peer-review activity – Pedagogical utilities (e.g., improving peer reviews and collaborative learning activities) n In situ learning and transfer across courses – Proxy label to train a model within the same course – Using labels obtained from past course data n Actionable predictions – While the course continues, vs. post-hoc approaches 60 Erkan Er, Eduardo Gómez-Sánchez, Miguel L. Bote-Lorenzo, Yannis Dimitriadis & Juan I. Asensio-Pérez (2020) Generating actionable predictions regarding MOOC learners’ engagement in peer reviews, Behaviour & Information Technology, 39:12, 1356-1373, DOI: 10.1080/0144929X.2019.1669222
Challenges and future directions n Human-centered design approaches are necessary to give voice to stakeholders and promote agency n Support to AI/LA-supported CSCL requires balanced and joint use of learning theories, data science, and design approaches n Mindsets of learners and teachers serve as promoters and obstacles of successful CSCL n Distributed scaffolding across tools, persons, and contexts is actual, promising and challenging 61
Take home messages n Collaboration has multiple relevant facets that require careful design to be successful n Teachers as designers and orchestrators of CSCL can and should be supported by tools n TEL-CSCL ecosystems are increasingly complex and AI/LA companions pose severe threats to agency 62

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yannis@collabtech_20221110_final.pptx

  • 1.
    Teachers as designersand orchestrators of technology- enhanced collaborative learning: Challenges and solutions Prof. Yannis Dimitriadis GSIC/EMIC group University of Valladolid, Spain CollabTech2022 10 November 2022
  • 2.
    Why collaboration matters(I) n Collaboration as a philosophical and political value – Value to consider in human-centered value-sensitive design n Collaboration as a learning/education mechanism – Mechanism to be understood, activated and optimized n Collaboration as a design target – Product and process to be designed for learning by teachers n Collaboration as a construct/concept – Construct to be estimated in Socially Shared Regulated Learning (SSRL) and co-RL n Collaboration as a social mechanism – Mechanism to be orchestrated in real-world classrooms 2
  • 3.
    Why collaboration matters(II) n Collaboration as a philosophical and political value – Value to consider in human-centered value-sensitive design – How can we design considering ethical/political values regarding the involved stakeholders? n Collaboration as a learning/education mechanism – Mechanism to be understood, activated and optimized – Is collaborative learning effective or how can it be more effective? n Collaboration as a design target – Product and process to be designed for learning by teachers – How can teachers (and other instructional designers) design for learning? 3
  • 4.
    Why collaboration matters(III) n Collaboration as a construct/concept – Construct to be estimated in Socially Shared Regulated Learning (SSRL) and co-RL – How can we measure theoretical concepts so that pedagogical interventions can be made? n Collaboration as a social mechanism – Mechanism to be orchestrated in real-world classrooms – What are the ways that teachers can put collaboration in practice and manage it in real-world contexts? 4
  • 5.
    A view ofthe TEL/CSCL ecosystem How to design for learning in it? 5
  • 6.
    Support teachers forcollaboration A contemporary technology-enhanced learning (TEL) ecosystem is complex, and collaboration is complex to achieve What are the conceptual and technological tools to support teachers as designers and orchestrators for Computer Supported Collaborative Learning (CSCL)? 6
  • 7.
    What is thistalk about (I) n How to design for effective and efficient (computer supported) collaborative learning? n How teachers as designers and orchestrators may be supported? – What are the main challenges and solutions regarding conceptual and technological support tools? n building on and adapting to existing design knowledge …. n Overview of patterns, approaches, tools, and systems that should respect teachers’ agency 7
  • 8.
    What is thistalk about (II) n Take advantage of complex computational approaches, typically based on artificial intelligence n Special attention to recent research on – How learning analytics solutions may be designed and implemented using human-centered approaches? – How socially shared regulated learning (SSRL) and co- regulation may be better supported? n Illustrating examples from the last 25 years n Prominent issues to guide future research 8
  • 9.
    Contents (I) n Somefundamental questions – Is (CS)CL effective in terms of learning outcomes? – Are there any (successful) patterns/scripts for (CS)CL? – What and how to design for (collaborative) learning? – How can teachers design and orchestrate for (CS)CL? n How to manage technology in CSCL contexts? – Collaboration management cycle – Technology for Collaboration – Distributed Scaffolding in complex CSCL ecosystems – Learning Analytics and AI for CSCL – From data to collaboration analytics – Human-Centered and Value-Sensitive Design 9
  • 10.
    Contents (II) n Examplesof models, tools, architectures, applications – Learning Design authoring and deployment tools – Dialogic Feedback: Framework and system – Detection and support of SSRL – Group Formation in MOOCs – Prediction and interventions in MOOCs – Detection of participatory roles n Challenges and future directions n Take home messages 10
  • 11.
    Is (CS)CL effective? nMeta-analytical evidence (Kollar et al., in prep) shows that CSCL is an effective way to foster learning, with moderate effect sizes on learning outcomes – Part of these effects can be attributed to the provision of computer support – Scaffold collaboration increases the effects of CSCL even more, for example through the provision of CSCL scripts – All these effects, however, seem to be moderated by distal variables such as the participants’ educational level, the domain of study, or the intervention duration n More meta-studies necessary for effects on learning processes, qualitative studies, technical papers 11 Kollar, I., Greisel, M., Özbek, T., Spang, L. & Vogel, F. (in prep.). Computer-supported collaborative learning. To be included in A. Gegenfurtner & I. Kollar (Eds.), Designing effective digital learning environments. Routledge.
  • 12.
    Patterns/scripts for (CS)CL? nEffective and efficient (CS)CL unlikely to occur – External obstacles (curriculum, competencies, cost, practical issues) – Psychological, social and technological issues (group formation and roles, need for collaboration, technology complexity, mindsets) n Pedagogical patterns/scripts to increase the chances for success n Support to design for successful (CS)CL 12
  • 13.
    (CS)CL (design) patterns Think-Pair-Share Think-Pair-Share(TPS) pattern – It structures collaboration and promotes participation in large classes They comment or take a classroom “vote” They pair and discuss their ideas about the question Each participant has time to think about the question 13
  • 14.
    (CS)CL (design) patterns Jigsaw/Puzzle Individualor initial group Teacher Introductory individual (or initial group) activity Collaborative activity around the sub-problem Collaborative activity around the problem and solution proposal Jigsaw pattern – It allows for individual accountability and positive interdependence
  • 15.
    (CS)CL Flow/assessment patterns 15 nLearning Flow n Assessment
  • 16.
    Aligning both setsof patterns 16
  • 17.
    Usefulness of patterns 17 nAre these patterns useful for practitioners? n Evidence for learning flow patterns for OER repurposing to collaborative activities n Appropriation in Higher Education teachers (Professional Development workshops) n But not always n If not included in appropriate technological tools n Too abstract for Primary Education practitioners n Do not consider enactment issues
  • 18.
    The need foratomic patterns 18 n Two independent studies by GSIC and SRI using Group Scribbles in schools n Studying enactment and disciplined improvisation n Showed that other small-scale, informal, contextual, actionable patterns emerged
  • 19.
    A learning designin action Orchestration graphs 19
  • 20.
    Use of pedagogical/designpattterns 20 What for? 1. Understand, compile and represent design knowledge (principles, patterns, procedures) 2. Empower and support teachers as designers (professional development) 3. Inform and embed design in tools and architectures (systems perspective)
  • 21.
    An orchestration framework 21 L.P.Prieto, Y. Dimitriadis, J.I. Asensio, C-K. Looi, “Orchestration in Learning Technology Research: Evaluation of a Conceptual Framework”, Research in Learning Technology (2015), 23: 28019 - http://dx.doi.org/10.3402/rlt.v23.28019 .
  • 22.
    Learning Design (LD) orDesign for Learning (D4L) - I n Learning is the objective of education – Can we (pedagogically) inform and (technologically) support teachers (and other stakeholders) in creating effective (and efficient?) learning situations n Main metaphor: – “Teachers as designers” n Main issue: – Is it possible that teachers (and other stakeholders) work as other traditional designers (e.g., architects, engineers)? – Can design form part of the normal flow of educational activities? 22
  • 23.
    Design for Learning– II “In media res framework” n What can be designed for learning? – The learning (performed by students) and support (made by teachers) tasks n The “physical” environment n Spaces, tools, infrastructures, artifacts-resources (to be consumed and/or produced) n The social architecture n Groupings, interactions with external agents n Design is indirect (tasks vs. activities) n Learners may change-interpret tasks in learntime 23 P. Goodyear, Y. Dimitriadis, “In medias res: reframing design for learning”, Research in Learning Technology, Research in Learning Technology Supplement (2013); 21: 19909 - http://dx.doi.org/10.3402/rlt.v21i0.19909 .
  • 24.
    Design for Learning– III “Activity-Centered Analysis and Design” (ACAD) 24 Goodyear, P., Carvalho, L. & Yeoman, P. Activity-Centred Analysis and Design (ACAD): Core purposes, distinctive qualities and current developments. Education Tech Research Dev 69, 445–464 (2021). https://doi.org/10.1007/s11423-020-09926-7
  • 25.
    Design for Learning Somenotes on the framework 25 n In the new real contexts n Teachers cannot resolve all emerging problems n There are many internal and external conditions n An equilibrium should be found between n Learners’ autonomy (“agency”) n Structuring and guiding (“structure, scripting”) n The process of D4L is nontrivial n Meet several objectives that are eventually contradictory
  • 26.
    Design for Learning(D4L) Some notes on the framework 26 n Who is going to control the learning process? n The teacher / designer n The student / learner n The devices / resources / virtual agents of the learning environment n D4L should look forward (forward-oriented design) in order to support the different phases n Configuration, orchestration, reflection, redesign ...
  • 27.
    Forward oriented design- I 27 n Design for Configuration: n Prepare, particularize, or modify what had been designed beforehand n Adapt to specific requirements of the context n Design for Orchestration n Support teachers (and students) at learn time Y. Dimitriadis, P. Goodyear, “Forward-oriented design for learning: Illustrating the approach”, Research in Learning Technology Supplement (2013), 21: 20290 - http://dx.doi.org/10.3402/rlt.v21i0.20290
  • 28.
    Forward oriented design- II n Design for Reflection n Be sure that monitoring can take place n Offer “awareness” at learn time n Allow for regulation and scaffolding n Inform evaluation of the intervention and assessment of learning n Design for Redesign n Take design decisions so that posterior modifications of the design can be made easily
  • 29.
    TinkerLamp Design for orchestration 29 Do-Lenh,S., Jermann, P., Legge, A., Zufferey, G., Dillenbourg, P. (2012). TinkerLamp 2.0: Designing and Evaluating Orchestration Technologies for the Classroom. In: Ravenscroft, A., Lindstaedt, S., Kloos, C.D., Hernández-Leo, D. (eds) 21st Century Learning for 21st Century Skills. EC-TEL 2012. Lecture Notes in Computer Science, vol 7563. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33263-0_6
  • 30.
  • 31.
    Spaces for collaboration Designphysical (and digital) environment 31
  • 32.
    Group concept maps Fullset of forward-oriented design 32 R. Martínez, Y. Dimitriadis, A. Martínez, J. Kay, K. Yacef “Capturing and analysing verbal and physical collaborative learning interactions at an enriched interactive tabletop”, International Journal of Computer Supported Collaborative Learning, 8(4), 455-485 (2013)
  • 33.
    Teaching as adesign science n “In media res”: Design forms part of the “normal flow” of educational activities n Teaching as a design science n Teaching is not only an art. It has a formally defined goal n It builds on design principles, rather than theories, and heuristics of practice than explanations n See also Design Based Research, co-design, … n Design patterns externalize knowledge and allow for discussion and sharing … Laurillard, D. (2018). Teaching as a Design Science: Teachers Building, Testing, and Sharing Pedagogic Ideas. In: Voogt, J., Knezek, G., Christensen, R., Lai, KW. (eds) Second Handbook of Information Technology in Primary and Secondary Education . Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-319-71054-9_108
  • 34.
    Supporting the D4Llifecycle Objectives, Activities … Students, resources, ICT tools… How to Enhance? Design for Learning lifecycle
  • 35.
    • Conceptualize • Author •Implement • Share • Evaluate • Explore Integrated Learning Design Environment http://ilde2.upf.edu The METIS ILDE The ILDE environment
  • 36.
    Example at UVA: “Landscapeorganization” (Geography)
  • 37.
    And the coursein Moodle!
  • 38.
    n ILDE – Itfits the needs of several educational contexts – It is independent from the pedagogical approach adopted – It covers all the phases of the LD lifecycle – It is usable by the ‘average’ teacher n Pedagogy is the “king” n Support is needed for enactment and communities beyond workshops Some METIS findings Some findings on ILDE J. I. Asensio, Y. Dimitriadis, F. Pozzi, D. Hernández, L.P. Prieto, D. Persico, S. Villagrá, “Towards Teaching as Design: exploring the interplay between full lifecycle Learning Design tooling and Teacher Professional Development”. Computers & Education, 114, 92-116 (2017).
  • 39.
    n First OrderBarriers – Lack of institutional support – Lack of adequate teacher training – Time/workload factors – Conceptual complexity of method and tools – Adoption by peers n Second order barriers – Use of ICTs in teaching practice – Teachers’ motivation Some METIS findings Barriers for adoption of LD F. M. Dagnino, Y. Dimitriadis, F. Pozzi, J.I. Asensio-Pérez, B. Rubia-Avi, “Exploring teachers’ needs and the existing barriers to the adoption of Learning Design methods and tools: a literature survey”, British Journal of Educational Technology, 49(6) 998-1013 (2018)
  • 40.
    Some METIS findings Lightweighttools for CSCL patterns The PyramidApp D. Manathunga, K., Hernández-Leo (2018), Authoring and enactment of mobile pyramid based collaborative learning activities, British Journal of Educational Technology, 49(2),262–275, doi:10.1111/bjet.12588
  • 41.
    Collaboration tools/resources n Buildingthe foundation or context for collaboration n Building interventions within contexts n Orchestrating student and teacher activities n Analyzing data 41 Rosé, C., Dimitriadis, Y. (2021). Tools and Resources for Setting Up Collaborative Spaces. In: Cress, U., Rosé, C., Wise, A.F., Oshima, J. (eds) International Handbook of Computer-Supported Collaborative Learning. Computer-Supported Collaborative Learning Series, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-030-65291-3_24.
  • 42.
    The collaboration managementcycle 42 Soller, A., Martínez-Monés, A., Jermann, P., Muehlenbrock, M. (2005) From Mirroring to Guiding: A Review of the State of the Art Technology for Supporting Collaborative Learning International Journal of Artificial Intelligence in Education (ijAIED). 15:261-290
  • 43.
    Distributed scaffolding 43 • Puntambekar,S. Distributed Scaffolding: Scaffolding Students in Classroom Environments. Educ Psychol Rev (2021). https://doi.org/10.1007/s10648-021-09636-3 • https://www.imec-int.com/en/research-portfolio/steams: Supporting TEAMS in ambient learning spaces Across 1. Tools and social scaffolds 2. Levels (individual, group, and whole class) 3. Time and Contexts
  • 44.
    Collaboration analytics (I) nCollaboration Analytics – Collocated, face-to-face groups, and platform-mediated groups (synchronous and asynchronous) – Help the team, educators, researchers or other stakeholders gain insights into the activity, and inform action that improves collaboration processes and products n Collaboration analytics require the integration of – (i) theoretically sound concepts – (ii) well designed tasks that generate useful data traces to inform analytics – (iii) human-centered design that empowers stakeholders to shape the analytics and produces effective user interfaces 44 Martinez-Maldonado, R., Gašević, D., Echeverria, V., Fernandez Nieto, G., Swiecki, Z., & Buckingham Shum, S. (2021). What Do You Mean by Collaboration Analytics? A Conceptual Model. Journal of Learning Analytics, 8(1), 126-153. https://doi.org/10.18608/jla.2021.7227.
  • 45.
    Collaboration analytics (II) 45 Martinez-Maldonado,R., Gašević, D., Echeverria, V., Fernandez Nieto, G., Swiecki, Z., & Buckingham Shum, S. (2021). What Do You Mean by Collaboration Analytics? A Conceptual Model. Journal of Learning Analytics, 8(1), 126-153. https://doi.org/10.18608/jla.2021.7227.
  • 46.
    Human-Centered Learning Analytics 46 Human-CenteredDesign should involve: Inclusion via stakeholder participation in the design process + Empathic experiences (particularly when making design decisions) Giacomin, J. (2014). What is human centred design? The Design Journal, 17(4), 606–623. https://doi.org/10.2752/175630614X140561854801.
  • 47.
    Levels of human-centeredness 47 SmuhaN.A. (2023). “Pitfalls and pathways for trustworthy Artificial Intelligence in education” in The Ethics of Artificial Intelligence in Education Practices, Challenges, and Debates, W. Holmes, K. Porayska-Pomsta (Eds). Taylor and Francis. n Human in command – Oversee when and how to use AI/ITS n Human on the loop – Participate in design and operation n Human in the loop – Get involved in every lifecycle phase
  • 48.
    Human-Centeredness in MMLA-AIED 48 Kukurova,M. (2022). “Multimodal Learning Analytics in Real-world Practice: A Bridge Too Far?”, Webinar at Spanish Network of Learning Analytics (SNOLA), May 2022. https://snola.es/2022/05/03/webinar-multimodal-learning- analytics-in-real-world-practice-a-bridge-too-far-mutlu-cukurova/
  • 49.
    Human-centered and trustworthyAI 49 • Delgado Kloos, C., et al. (2022), H2O Learn - Hybrid and Human-Oriented Learning: Trustworthy and Human- Centered Learning Analytics (TaHCLA) for Hybrid Education. IEEE Global Engineering Education Conference, EDUCON 2022, • HLEG-AI (High-Level Expert Group on Artificial Intelligence) (2019), “Ethics Guidelines for Trustworthy AI: Requirements of Trustworthy AI,” Available: https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines/1
  • 50.
  • 51.
    LA-based orchestration toolsfor CSCL Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance 51 n Orchestration tools build upon learning analytics n Information that could be adapted to the specific situation n Detrimental effects if not tailored to a teacher’s needs n Teachers in the advising condition more often detected the problematic group, needed less effort to do so, and were more confident of their decisions Anouschka van Leeuwen, Nikol Rummel. 2020. Comparing Teachers’ Us of Mirroring and Advising Dashboards. In Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK’20). ACM, New York, NY, USA, X pages.
  • 52.
    Collaborative Dialogic Feedback(I) Framework 52 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): A collaborative learning approach to dialogic peer feedback: a theoretical framework, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1786497
  • 53.
    Dialogic Feedback (II) Designprinciples n Connect self-evaluation with peer evaluations n Provide opportunities to resolve the discrepancies in students’ perspectives about the quality of the work n Provide mechanisms to (collectively) plan the feedback before its provision n Enable dialogue around the feedback to support its uptake n Enable students to set goals and create an action plan with peers based on the feedback n Enable dialogue with peers while students are revising their work 53 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): A collaborative learning approach to dialogic peer feedback: a theoretical framework, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1786497
  • 54.
    Dialogic feedback (III) TheSynergy system 54 Erkan Er, Yannis Dimitriadis & Dragan Gašević (2020): Collaborative peer feedback and learning analytics: theory-oriented design for supporting class-wide interventions, Assessment & Evaluation in Higher Education, DOI: 10.1080/02602938.2020.1764490
  • 55.
    Socially Shared RegulatedLearning (I) 55 Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance Socially-Shared Regulation of Learning Cognitive Metacognitive Motivation Emotions
  • 56.
    Socially Shared RegulatedLearning (II) To extract meaningful SSRL indicators from trace data to support groups during collaboration Cristina Villa-Torrano How have we incorporated SSRL phases in the design? Task Understanding Setting Goals & Planning, Adaptation Task Enactment 56
  • 57.
    Socially Shared RegulatedLearning (III) Cristina Villa-Torrano Examining the relationship between groups’ engagement within SSRL Docs and performance Which data sources do we have to extract meaningful information? 57
  • 58.
    Detection/adaptation of roles 58 J.A.Marcos, A. Martínez, Y. Dimitriadis, “DESPRO: A method based on roles to provide collaboration analysis support adapted to the participants in CSCL situations”, Computers & Education, 82 235-253 (2015)
  • 59.
    Group Formation inMOOCs n Support for CSCL in MOOCs (guide and tool) n Design guide allowed teachers – Be aware of the contextual factors to consider when forming the collaborative groups – Be informed about some configuration parameters of the activity and the group formation n Strategy with higher degree of homogeneity – Grouped students with similar levels of engagement – Achieved best results in terms of group performance, group interactions and student satisfaction 59 Luisa Sanz-Martínez, Erkan Er, Alejandra Martínez-Monés, Yannis Dimitriadis & Miguel L. Bote-Lorenzo (2019) Creating collaborative groups in a MOOC: a homogeneous engagement grouping approach, Behaviour & Information Technology, 38:11, 1107-1121, DOI: 10.1080/0144929X.2019.1571109
  • 60.
    Prediction/interventions in MOOCs nPredictive models – Accurately classify learners according to their expected engagement levels in an upcoming peer-review activity – Pedagogical utilities (e.g., improving peer reviews and collaborative learning activities) n In situ learning and transfer across courses – Proxy label to train a model within the same course – Using labels obtained from past course data n Actionable predictions – While the course continues, vs. post-hoc approaches 60 Erkan Er, Eduardo Gómez-Sánchez, Miguel L. Bote-Lorenzo, Yannis Dimitriadis & Juan I. Asensio-Pérez (2020) Generating actionable predictions regarding MOOC learners’ engagement in peer reviews, Behaviour & Information Technology, 39:12, 1356-1373, DOI: 10.1080/0144929X.2019.1669222
  • 61.
    Challenges and futuredirections n Human-centered design approaches are necessary to give voice to stakeholders and promote agency n Support to AI/LA-supported CSCL requires balanced and joint use of learning theories, data science, and design approaches n Mindsets of learners and teachers serve as promoters and obstacles of successful CSCL n Distributed scaffolding across tools, persons, and contexts is actual, promising and challenging 61
  • 62.
    Take home messages nCollaboration has multiple relevant facets that require careful design to be successful n Teachers as designers and orchestrators of CSCL can and should be supported by tools n TEL-CSCL ecosystems are increasingly complex and AI/LA companions pose severe threats to agency 62