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PBL, Transfer and New Media
@DrBartRienties
Reader in Learning Analytics
11th of December 2015Dublin
FACiLiTATE Employability and Transfer - E/PBL research and practice Seminar
Innovative Pedagogy 2015 report out!!! http://www.open.ac.uk/blogs/innovating/
Crossover learningConnecting formal and informal learningLearning through argumentationDeveloping skills of scientific argumentationIncidental learningHarnessing unplanned or unintentional learningContext-based learningHow context shapes and is shaped by the process of learningComputational thinkingSolving problems using techniques from computingLearning by doing science with remote labsGuided experiments on authentic scientific equipmentEmbodied learningMaking mind and body work together to support learningAdaptive teachingAdapting computer-based teaching to the learner’s knowledge and actionAnalytics of emotionsResponding to the emotional states of studentsStealth assessmentUnobtrusive assessment of learning processes
(Social) Learning Analytics“LA is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” (LAK 2011)
Social LA “focuses on how learners build knowledge together in their cultural and social settings” (Ferguson & Buckingham Shum, 2012)
A) Role of informal learning in PBL Medical programme
C) How do students choose collaboration PBL tools?B Learning analytics with
120+ variables in PBL Math course
Informal learning• Medical programme• 1st year students• Face-to-Face• Measurements after 4 months studying• Problem-Based Learning• N=302
Hommes, J., Rienties, B., de Grave, W., Bos, G., Schuwirth, L., Scherpbier, A. (2012). Visualising the invisible: a network approach to reveal the informal social side of student learning. Advances in Health Sciences Education. 17(5), 743-757. Impact factor: 2.089.
Formal and Informal Interaction between learners and teachers crucial for learning processes and outcomes (DeCuyper et al., 2010; Giesbers, Rienties, et al., 2013; Hommes, Rienties et al, 2012; Rienties et al., 2012, 2013a, 2013b)
Hommes, J., Rienties, B., de Grave, W., Bos, G., Schuwirth, L., Scherpbier, A. (2012). Visualising the invisible: a network approach to reveal the informal social side of student learning. Advances in Health Sciences Education. 17(5), 743-757. Impact factor: 2.089.
Not significant
Not significant
Rienties, B., Hernandez Nanclares, N., Hommes, J., & Veermans, K. (2014). Understanding emerging knowledge spillovers in small-group learning settings; a networked learning perspective. In V. Hodgson, M. De Laat, D. McConnell & T. Ryberg (Eds.), The Design, Experience and Practice of Networked Learning (Vol. 7, 127-148) Springer: Dordrecht.
Learn more inside assigned group
Learn more outside group
Learn outside group
80% occurs outside formal classroom
Hommes, J., Arah, O. A., de Grave, W., Bos, G., Schuwirth, L., & Scherpbier, A. (2014). Medical students perceive better group learning processes when large classes are made to seem small. PLOS One, 9(4), e93328. doi: 10.1371/journal.pone.0093328
Hommes, J., Arah, O. A., de Grave, W., Bos, G., Schuwirth, L., & Scherpbier, A. (2014). Medical students perceive better group learning processes when large classes are made to seem small. PLOS One, 9(4), e93328. doi: 10.1371/journal.pone.0093328
Hommes, J., Arah, O. A., de Grave, W., Bos, G., Schuwirth, L., & Scherpbier, A. (2014). Medical students perceive better group learning processes when large classes are made to seem small. PLOS One, 9(4), e93328. doi: 10.1371/journal.pone.0093328
Introduction math/stats
• Business• 1st year students• Blended• 0-12 weeks after start studying• Adaptive learning/Problem-Based
Learning• N=990
DiagnosticEntryTests
Week 0 Week 1 Week 2 Week 3 Week 4 Week 6Week 5
Quiz 1 Quiz 2 Quiz 3
Final Exam
• Math-Exam
• Stats-Exam
--------------------------------------------- BlackBoard LMS behaviour -----------------------------------------
Week 7
Mastery scores MyMathlab
Mastery scores
Practice time # Attempts
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores MyMathlab
Practice time # Attempts
Mastery scores MyStatlab
Mastery scores
Practice time # Attempts
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores
Practice time# Attempts
Mastery scores MyStatlab
Practice time# Attempts
Demogra-phic data
QMTotal
Week 8
Learning Styles, Motivation,
Engagement
Learning Emotions -Learning dispositions ------------------ ------------------------------------------------------------------
Tempelaar, D., Rienties, B., Giesbers., B. (2015). In search for the most informative data for feedback generation: Learning Analytics in a data-rich context. Computers in Human Behaviour. 47, 157-167. Impact factor: 2.067.
LMS prediction Not great
E-tutorials prediction Substantial improvement!
Entry test and quizes Even better!
All elements combined:
Using track data we can follow: -who is struggling?-where?-when?-why?
Who is struggling in week 3?
What can be done about this?• (Personalised) feedback• (Personalised) examples• Peer support• Emotional/learning support
Online acculturation/introduction course Economics• Economics/acculturation• (Nearly) 1st year international students• Distance Education• -6 – 0 weeks before starting @uni• Problem-Based Learning• N=110
Dynamic interaction of sychronous and asychronous learning
Giesbers, B., Rienties, B., Tempelaar, D.T., & Gijselaers, W. H. (2014). A dynamic analysis of the interplay between asynchronous and synchronous communication in online learning: The impact of motivation. Journal of Computer Assisted Learning, 30(1), 30-50. Impact factor: 1.632.
Intrinsic Motivation ↑ initial asynchronous contributions ↑ in asynchronous and synchronous contributions
Giesbers, B., Rienties, B., Tempelaar, D.T., & Gijselaers, W. H. (2014). A dynamic analysis of the interplay between asynchronous and synchronous communication in online learning: The impact of motivation. Journal of Computer Assisted Learning, 30(1), 30-50. Impact factor: 1.632.
Is data from Virtual Learning Environment systems (e.g., Blackboard, Moodle) useful for learning (analytics) and PBL? What else should we focus on to improve our understandings of social interaction?
• “Raw” VLE data does not seem very useful
• (entry)quizzes/formative learning outcomes in combination with learning dispositions provide good early-warning systems
Implications for EURO CALLHow can we make learning more personalised, adaptive and meaningful, and what are the implications for PBL?• What about informal learning?• Individual differences? Learning
dispositions?• Emotions? • Ethics?
PBL, Transfer and New Media
@DrBartRienties
Reader in Learning Analytics
11th of December 2015Dublin
FACiLiTATE Employability and Transfer - E/PBL research and practice Seminar
