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Assessing Students and Tutors with Learning Analytics Dashboards
The document details a webinar discussing the use of learning analytics dashboards to assess students and tutors, highlighting trends in big data and learning analytics. It covers various analytics approaches, tools, and methodologies, including techniques for analyzing student engagement and performance. The document also emphasizes the importance of data storytelling and the evolving landscape of higher education.
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Similar to Assessing Students and Tutors with Learning Analytics Dashboards
Assessing Students and Tutors with Learning Analytics Dashboards
- 1. Assessing Students andTutors with Learning Analytics Dashboards Vassilios S. Verykios, Professor Hellenic Open University, Greece [email protected] FREE webinar, 26 September 2017 11.00 – 12.00 (CEST)
- 2. Assessing Students andTutors with Learning Analytics Dashboards Outline • Big Data, Data Mining & Learning Analytics • The HOU Data Ecosystem • Learning Analytics Approaches and Tasks • Experiments and Results • Conclusions
- 3. Assessing Students andTutors with Learning Analytics Dashboards The PYTHIA Recommender System • A framework and a software system • Provides solutions in terms of scientific inquiries • Selection of HW/SW artifacts in PSEs • Quickest and most efficient solution
- 4. Assessing Students andTutors with Learning Analytics Dashboards Revolution in Higher Education • Outlines the problems HEIs are facing today • Colleges and universities are becoming insufferably costly • Incapable of sustaining their existence • Many graduates lack necessary skills Richard Allan DeMillo
- 5. Assessing Students andTutors with Learning Analytics Dashboards The Petabyte Age • An era of rapidly developing technology • Information is gathered at an ever increasing rate • Capture, store analyze this wealth of data • Determine how successful we are in the future
- 6. Assessing Students andTutors with Learning Analytics Dashboards The Big Data Era • A field of immense interest • Store and index data • Analyze and utilize in an efficient way • Answers to most problems Big data is everywhere – but does it have the solution?
- 7. Assessing Students andTutors with Learning Analytics Dashboards The End of Theory Chris Anderson • An author and an entrepreneur, former editor of Wired Magazine • Shift in the way we look at data • Rather than developing a theory • Look for patterns, outliers, …
- 8. Assessing Students andTutors with Learning Analytics Dashboards Data Mining Ronny Kovahi, Crossing the Chasm: From Academic Machine Learning to Commercial Data Mining, ICML 1998
- 9. Assessing Students andTutors with Learning Analytics Dashboards CRoss Industry Standard Process • Describes the commonly used approaches by data mining experts • Breaks the process of data mining onto six major phases • Determining the problem, preparing the data, etc.
- 10. Assessing Students andTutors with Learning Analytics Dashboards Truth and Lies about how Students Study • Simple statistics, questionnaires and surveys • People’s answers are not always consistent with the reality • People lying/cheating, being embarrassed • Brain scanning test
- 11. Assessing Students andTutors with Learning Analytics Dashboards Data Storytelling • The Essential Data Science Skill Everyone Needs • Not simply data visualization or analytics reporting • A blending of “hard data” and “human communication” • Help marketers achieve their goals
- 12. Assessing Students andTutors with Learning Analytics Dashboards Definition(s) of Learning Analytics • “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environment (s) in which it occurs” - Siemens, G., 2011 • “is about collecting traces that learners leave behind and using those traces to improve learning” - Erik Duval E., 2012 • “the use of data, which may include ‘big data’, to provide actionable intelligence for learners and teachers” – Ferguson R., 2014
- 13. Assessing Students andTutors with Learning Analytics Dashboards Evolution of Trends • “Data Mining” and “Data Analysis” give place to “Data Science” and “Big Data” • “Learning Analytics” are still premature
- 14. Assessing Students andTutors with Learning Analytics Dashboards State of the Art in Learning Analytics • Create software, services and applications • Forecast – a Purdue- developed student success app • Develop habits and behaviors
- 15. Assessing Students andTutors with Learning Analytics Dashboards The Hellenic Open University (HOU) story • Officially established in 1997 • The only University in Greece that exclusively offers “distance” education programs • Four Schools (Humanities, Social Sciences, Science and Technology, and Applied Arts) • > 40 programs • ≈ 50 faculty members, 2000 Adjunct lecturers/instructors, 40K students, 220 employees, 12 km2 building facilities
- 16. Assessing Students andTutors with Learning Analytics Dashboards The HOU Core System Infrastructure Students Information System (open.eap.gr) The Learning Management System (study.eap.gr) The Educational Material Repository (apothesis. eap.gr) The web teleconference system (centra.eap.gr)
- 17. Assessing Students andTutors with Learning Analytics Dashboards Studying in HOU • Each program consists of modules which comprise of up to three regular university courses • Each module includes five optional face-to-face group sessions that take place in approx. 9 cities in Greece • Students have to submit 4-6 written assignments throughout the academic year period at the end of which they participate in a compulsory written exam
- 18. Assessing Students andTutors with Learning Analytics Dashboards Our case study • Student Admission data (1M records) during 2003 - 2013 • Bachelor in Computer Sciences • Principles of Software Engineering (PLI11) module • Master’s in Information Systems • Specialization in Theory & Software (PLS50) module • Specialization in Software Engineering (PLS60) module • Code - Create - Learn with Scratch (Scratch Coding)
- 19. Assessing Students andTutors with Learning Analytics Dashboards Learning Analytics Approaches • Non-native approaches • Data migration • More options available • Entails dangers • Scalability of the process • Native approaches • Process data in the origin • Easier and requires no specialist knowledge • Can run on real time • Limited options
- 20. Assessing Students andTutors with Learning Analytics Dashboards Learning Analytics Tasks Classification Clustering Decision Trees Text Mining Social Network Analysis Sentiment Analysis Sequential Mining
- 21. Assessing Students andTutors with Learning Analytics Dashboards Learning Analytics Tools
- 22. Assessing Students andTutors with Learning Analytics Dashboards Learning Analytics Dashboards • Device Analytics • Completion Progress • Course Dedication • Forum Graph Report • Graph Analytics Block • Configurable Report
- 23. Assessing Students andTutors with Learning Analytics Dashboards Device Analytics Provides a quick overview of users’ used devices. • Device type • Operating System • Browser (version logging) • Display and Window size • Input type (mouse, touchscreen)
- 24. Assessing Students andTutors with Learning Analytics Dashboards Configurable Report • A custom reports builder • Based on SQL queries on Moodle Database Scheme • No SQL knowledge is required?! • Suitable for admins or teachers • Several types of reports: Courses, Categories, Users, Timeline reports, Custom SQL reports
- 25. Assessing Students andTutors with Learning Analytics Dashboards Moodle Database Schema
- 26. Assessing Students andTutors with Learning Analytics Dashboards Completion Progress A time-management tool • Relies on completion settings of activities/resources in the course • Visual representation of activities to be completed • Color-coded for quick reference • Overview for teachers, identify students at risk
- 27. Assessing Students andTutors with Learning Analytics Dashboards Course Dedication Allow teachers to keep track of estimated dedication time of students in a course • Time is estimated based on • Clicks, Sessions, and Sessions Duration • Offers views of dedication time of • The course, in total • A group of students • An individual student
- 28. Assessing Students andTutors with Learning Analytics Dashboards Forum Graph Report Analyze the interactions between participants in a forum activity • Each node is a user • the size depends on the no. of posts • Each edge represents the interaction between 2 users • Thickness indicates the no. of replies • Arrow indicates who was replying
- 29. Assessing Students andTutors with Learning Analytics Dashboards Graph Analytics Provides graphs that facilitate the identification of student profiles • Grades Chart • Content Access Chart • Active Users Chart • Assignment Submissions Chart • Hits Distribution Chart Graphs allow teachers to message students according to their behavior in the course
- 30. Assessing Students andTutors with Learning Analytics Dashboards Analyzing Admission Data * Created using Python
- 31. Assessing Students andTutors with Learning Analytics Dashboards Analyzing Admission Data * Created using Tableau v. 9.3 * Created using Python
- 32. Assessing Students andTutors with Learning Analytics Dashboards Customized Reports • Customized reports based on Moodle SQL scheme • Knowledge of Database Internal Organization is Required * Created using Moodle Configurable Reports plugin
- 33. Assessing Students andTutors with Learning Analytics Dashboards Students Performance Visualization Analytics graph for grades distribution of written and online assignments * Created using Moodle Forum Graph plugin
- 34. Assessing Students andTutors with Learning Analytics Dashboards Visualizing Students’ Submissions Assignments and Quizzes submission graphs * Created using Moodle Forum Graph plugin
- 35. Assessing Students andTutors with Learning Analytics Dashboards Measuring Engagement with the Platform Tutors’ course dedication time Tutors’ connections per day Students’ dedication info * Created using Moodle Course Dedication plugin
- 36. Assessing Students andTutors with Learning Analytics Dashboards Measuring Engagement with the Content Online tests and content access distribution graphs * Created using Moodle Forum Graph plugin
- 37. Assessing Students andTutors with Learning Analytics Dashboards Students’ Activity Visualization The distribution of active students and students’ activities to daily hours * Created using Moodle Analytics Graphs plugin
- 38. Assessing Students andTutors with Learning Analytics Dashboards Monitoring Activity Completion Student’s progress bar Tutor’s overview page * Created using Moodle Completion Progress plugin
- 39. Assessing Students andTutors with Learning Analytics Dashboards Text Mining in Forum Data * Created using R packages
- 40. Assessing Students andTutors with Learning Analytics Dashboards Forum Participation & Frequent Threads * Created using R packages
- 41. Assessing Students andTutors with Learning Analytics Dashboards Monitoring Participation in Forums The PLI11 Module forum graph An integrated view of the groups forum graph * Created using Moodle Forum Graph plugin
- 42. Assessing Students andTutors with Learning Analytics Dashboards Monitoring Participation in Forums Tutors’ activity in Tutors’ forum of PLI11 * Created using Moodle Forum Graph plugin
- 43. Assessing Students andTutors with Learning Analytics Dashboards Identifying Polarity in Discussion Fora * Created using R packages
- 44. Assessing Students andTutors with Learning Analytics Dashboards Identifying Emotion in Discussion Fora * Created using R packages
- 45. Assessing Students andTutors with Learning Analytics Dashboards References • Richard A. DeMillo, Revolution in Higher Education: How a Small Band of Innovators Will Make College Accessible and Affordable, MIT Press, 2015 • Martin Lindstrom, Buyology: Truth and Lies About Why We Buy, 2010 • Chris Anderson, The end of theory: the data deluge makes the scientific method obsolete, WIRED Science, 06.23.08 • The Petabyte Age: Because more isn’t just more – more is different, WIRED Science, 06.23.08 • Stephen Baker, The Numerati, Houghton Mifflin Company, 2009 • Brent Dykes, Data Storytelling: The Essential Data Science Skill Everyone Needs, Forbes, 03.31.16 • Ronny Kovahi, Crossing the Chasm: From Academic Machine Learning to Commercial Data Mining, ICML 1998
- 46. Assessing Students andTutors with Learning Analytics Dashboards References • E. Lotsari, V.S. Verykios, C.T. Panagiotakopoulos, and D. Kalles. A Learning Analytics Methodology for Student Profiling, Proc. of the 8th Hellenic Conference on Artificial Intelligence, 2014. • V. Kagklis, A. Karatrantou, M. Tantoula, C.T. Panagiotakopoulos, and V.S. Verykios. A learning analytics methodology for detecting sentiment in student fora: A Case Study in Distance Education. European Journal of Open, Distance and E-learning, 2014. • V. Kagklis, A. Lionarakis, E.C. Stavropoulos, and V.S. Verykios. A Learning Analytics Methodology for Student Performance Assessment in a Distance and Open Education Environment, Proc. of EADTU annual conference, 2016. • A.F. Gontzis, C.V. Karachristos, C.T. Panagiotakopoulos, E.C. Stavropoulos, and V.S. Verykios, Sentiment Analysis to track Emotion and Polarity in Student Fora, Proc. of PCI 2017. • A.F. Gontzis, C.T. Panagiotakopoulos, E.C. Stavropoulos, and V.S. Verykios, A Holistic View on Academic Wide Data through Learning Analytics Dashboards, Proc. of EADTU annual conference 2017. • V. Kagklis, A. Lionarakis, G. Marketos, C.T. Panagiotakopoulos, E.C. Stavropoulos, and V.S. Verykios. Student Admission Data Analytics for Open and Distance Education in Greece. Open Education - The Journal for Open and Distance Education and Educational Technology, 2017.
- 47. Assessing Students andTutors with Learning Analytics Dashboards Monitoring Students’ Engagement Hits Distribution Charts * Created using Moodle Forum Graph plugin
- 48. Assessing Students andTutors with Learning Analytics Dashboards Social Network Analysis of Students Fora Students and Tutors’ interaction in online forum. The size of nodes indicates the degree of participation. The threads each student (turquoise) participates in, along with the number of different students involved in each thread (purple).* Created using R packages
- 49. Assessing Students andTutors with Learning Analytics Dashboards Sentiment Classification Sentiment classification of students messages Sentiment classification of Tutors’ messages * Created using Niosto
Editor's Notes
- #6 Sensors everywhere. Infinite storage. Clouds of processors. Our ability to capture, warehouse, and understand massive amounts of data is changing science, medicine, business and technology. As our collection of facts and figures grows, so will the opportunity to find answers to fundamental questions. Because in the era of big data, more isn’t just more. More is different.
- #7 Big Data: data sets which are so large or complex making traditional data processing applications inadequate to deal with them
- #8 Computers, algorithms, and big data can potentially generate more insightful, useful, accurate, or true results than specialists or domain experts who traditionally craft carefully targeted hypotheses and research strategies.
- #11 A best seller book, by Martin Lindstrom Analyses what makes people buy in a world which is cluttered with messages (advs, slogans, jingles, celebrities, shows, etc.) A three year and $7M research on 2000 consumers’ brains …Everything we believe about why we buy is wrong…
- #12 A best Seller book, by Cole Nussbaumer Knaflic Demonstrates how to use your data to create an engaging, informative, compelling story
- #28 Click: every time that a user access to a page in Moodle a log entry is stored. Session: set of two or more consecutive clicks in which the elapsed time between every pair of consecutive clicks does not overcome an established maximum time. Session duration: elapsed time between the first and the last click of the session.