Learning Analytics as a Research Method: a hands-on teaser
1
Learning Analytics as a Research Method: a hands-on teaser Manolis Mavrikis and Wayne Holmes Research Methods (Education and Technology MA) * London Knowledge Lab, Culture Communication and Media, UCL IOE This poster reflects on a hands-on MA session that was designed as a response to the emergence of the fields of Learning Analytics and Educational Data Mining. • The methods and techniques from this area are usually perceived as applied research in Technology-Enhanced Learning. • The aim of the MA session was to help students appreciate the role of such methods as complementary to design- based, qualitative or other quantitative paradigms that are traditionally taught in this course. To overcome the initial cognitive load and barriers to understanding Learning Analytics techniques we provide data sets and ‘half-baked’ processes in RapidMiner, a tool for conducting exploratory data analysis and Weka, a collection of machine learning algorithms for data mining tasks.. Learning Analytics is “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Society for Learning Analytics Research). Educational Data Mining is “an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings in which they learn” (EducationalDataMining.org). This approach relates to the research and enquiry strands of the Connected Curriculum initiative, which aims to ensure all UCL students are able to learn through participating in professional research. We enable students to research in Learning Analytics by connecting to funded projects (such as the EU FP7 funded iTalk2Learn and M C Squared) that provide appropriate contexts and data sets. I am looking for evidence of learning. Weka Bayesian Model: ‘Need for help • We would like to thank Dr Mina Vasalou (London Knowledge Lab), who is leading the Research Methods in Educational Technology module this year, for her help and support in preparing the online materials and for ensuring the smooth running of the workshop. • Datasets relate to the EUT FP7 projects iTalk2Learn (#318051) and M C Squared (#610467) and previous research in M. Mavrikis (2010). Modelling Student Interactions in Intelligent RapidMiner process and decision trees output
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Transcript of Learning Analytics as a Research Method: a hands-on teaser
Learning Analytics as a Research Method: a hands-on teaser Manolis Mavrikis and Wayne Holmes
Research Methods (Education and Technology MA)*
London Knowledge Lab, Culture Communication and Media, UCL IOE
This poster reflects on a hands-on MA session that was designed as a response to the emergence of the fields of Learning Analytics and Educational Data Mining.
• The methods and techniques from this area are usually perceived as applied research in Technology-Enhanced Learning.
• The aim of the MA session was to help students appreciate the role of such methods as complementary to design-based, qualitative or other quantitative paradigms that are traditionally taught in this course.
To overcome the initial cognitive load and barriers to understanding Learning Analytics techniques we provide data sets and ‘half-baked’ processes in RapidMiner, a tool for conducting exploratory data analysis and Weka, a collection of machine learning algorithms for data mining tasks..
Learning Analytics is “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Society for Learning Analytics Research).
Educational Data Mining is “an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings in which they learn” (EducationalDataMining.org).
This approach relates to the research and enquiry strands of the Connected Curriculum initiative, which aims to ensure all UCL students are able to learn through participating in professional research. We enable students to research in Learning Analytics by connecting to funded projects (such as the EU FP7 funded iTalk2Learn and M C Squared) that provide appropriate contexts and data sets.
I am looking for evidence of
learning.
Weka Bayesian Model: ‘Need for help
• We would like to thank Dr Mina Vasalou (London Knowledge Lab), who is leading the Research Methods in Educational Technology module this year, for her help and support in preparing the online materials and for ensuring the smooth running of the workshop.
• Datasets relate to the EUT FP7 projects iTalk2Learn (#318051) and M C Squared (#610467) and previous research in M. Mavrikis (2010). Modelling Student Interactions in Intelligent Learning Environments: Constructing Bayesian Networks from Data. In International Journal on Artificial Intelligence Tools (IJAIT), 19(6):733--753.
RapidMiner process and decision trees output
