In this guest lecture, Geraldine gave an overview of the genesis and practice of learning analytics in higher education in Ireland and beyond

Gray, Geraldine, Dr

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ARC (Academic Research Collection) (College Dubin)

CCT College Dublin ARC (Academic Research Collection) Certificate in Teaching and Learning CCT Centre for Teaching and Learning 4-20-2020 How Can I use Learning Analytics in my Teaching Practice Geraldine Gray Dr Technical University Dublin Follow this and additional works at: https://arc.cct.ie/cert_tl  Part of the Higher Education Commons Recommended Citation Gray, Geraldine Dr, "How Can I use Learning Analytics in my Teaching Practice" (2020). Certificate in Teaching and Learning. 7. https://arc.cct.ie/cert_tl/7 This Presentation is brought to you for free and open access by the CCT Centre for Teaching and Learning at ARC (Academic Research Collection). It has been accepted for inclusion in Certificate in Teaching and Learning by an authorized administrator of ARC (Academic Research Collection). For more information, please contact jsmyth@cct.ie. How can I useLearning Analyticsin my teaching practice?Dr. Geraldine GrayTU DublinCCT, Nov 2019Outline1. What is Learning Analytics?2. Our Data….and what we can do with it3. Some of the pitfalls….and benefits4. How do I get started….and what supports do I need?Learning analytics: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. (SoLAR – Society for Learning Analytics Research)Data ScienceSocial Network analysisAldowah, H., Al-Samarraie, H., & Fauzy, W. M. (2019). Educational Data Mining and Learning Analytics for 21stcentury higher education: A Review and Synthesis. Telematics and Informatics.Learning analytics for 21st century HEGoals of learning analytics: Is it to….?Improve statistics on student disengagement, retention, progression . . .Nurture  the skills and dispositions, assessed under authentic conditions, that equip learners to cope with novel, complex situations. Developed capacity for learning to learn rather than learn to pass exams Prepare students for the world they will work inSimon Buckingham Shum and Ruth Deakin Crick (2016). Learning analytics for 21st century competencies. Journal of Learning Analytics, 3(2), 6–21.Two distinct trajectories . . .Predictive tool to identify at risk students Model of implementation: a technical solution Provision of data to prompt action from educator Facilitate student engagement with existing model of learningDevelop understanding of, and improvements in, teaching and learning  More complex model of implementation Bring understanding to learning and teaching practices  Disruption and innovation to improve the quality of the student learning experience G. Gray6Colvin, Cassandra, et al. "Student retention and learning analytics: A snapshot of Australian practices and a framework for advancement." Sydney: Australian Office for Learning and Teaching (2015).Learning Analytics as an enabler of high quality educationHershkovitz A., Knight S., Dawson S., Jovanovid J., Gaševid, D. (2016) About “learning” and “analytics”. Journal of Learning Analytics, 3(2), 1–5Analysis of skills correlated with assessment results:Non-cognitive factors that correlate with assessment results indicate the skills and competencies we valueG. Gray8Deep learners?What can be measured?The easy stuff: Exam grades Attendance Enrollment data Logs of activities on Virtual Learning Environments (VLE)Latent constructs: Learning itself Effective learning disposition: persistence; self-regulation; deep learning; creativity; . . .. Affective state: boredom, engagement Overt measurements:Academic history and self reporting questionnairesG. Gray11Cassidy, Simon. "Exploring individual differences as determining factors in student academic achievement in higher education." Studies in Higher Education 37.7 (2012): 793-810.Online behaviour on VLEs (and ITSs)G. Gray12 The number of days a student accesses the system The number of logins The amount of time spent logged in The number of posts viewed The number of posts writtenLowes, Susan, Peiyi Lin, and Brian Kinghorn. "Exploring the link between online behaviours and course performance in asynchronous online high school courses." Journal of Learning Analytics 2.2.Early alert systemsG. Gray13Curriculum designG. Gray14Students facing analyticsG. Gray15Comparison to class averageG. Gray16Comparison to class averageG. Gray17Nottingham Trent UniversityAdaptive learningG. Gray18Stealth measurementWhat can be implied from behaviourObjective . . . Measurement of constructs that are ill-defined, such as creativity, collaborative learning, self-regulated learning, or persistence:21st century skillsHershkovitz A., Knight S., Dawson S., Jovanovid J., Gaševid, D. (2016) About “learning” and “analytics”. Journal of Learning Analytics, 3(2), 1–5Analysis of reflective text for evidence of metacognitionInitial results are promising .  . .Gibson, Kitto, Bruaza, (2016). Towards the discovery of learner metacognition from reflective writing. Journal of Learning Analytics, 3(2), 22–36.Behavioral data extracted from keystroke analysesAllen et. al. (2016), {ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke Analyses, 9th International Conference on Educational Data Mining, Raleigh, NC, June 2016The Eyes Have It: Gaze-based Detection of Mind Wandering during LearningModest results to date . . .Hutt et. al. (2016), {ENTER}ing the Time Series {SPACE}: Uncovering the Writing Process through Keystroke Analyses, 9th International Conference on Educational Data Mining, Raleigh, NC, June 2016 Game based ITS offer players a lot of choice Analysis of pathways through a game’s choices can categories behaviour as organised/systematic or disorganised. Directly related to self-regulationG. Gray24Snow, Erica, et al. "Entropy: A stealth measure of agency in learning environments." Educational Data Mining 2014.Gaming in education: Self regulation measured via pathways chosenData that is not about student . . . What about our learning resources?Predict ‘Liveliness’ in Educational VideosOnline educational videos have emerged as one of the most popular modes of learning in the recent years. Studies have shown that liveliness is highly correlated to engagement in educational videos.Sharma et. al. (2016), LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos 9th International Conference on Educational Data Mining, Raleigh, NC, June 2016Prof. Alyssa Wise, NYU; SoLAR seminar series, Oct 2019 https://www.youtube.com/watch?v=VF1IkC6DJl8Some limitations . . . "There are three kinds of lies: lies, damned lies,  and statistics.”British Prime Minister Benjamin DisraeliIs it correct or useful to depicting people as a vector of number?Age Gender CAO points 1st year GPA27 0 240 3.7Street light effect . . .Interpreting information correctlyCan people be pigeon-holed?The wrong feedback?“Giving mastery oriented students information about their poor performance relative to the rest of the class, it reduced their mastery behaviour and promoted shallow learning behaviour.”G. Gray33What is the right feedback?Privacy and ethics in Learning AnalyticsG. Gray34Ferguson, Rebecca, et al. "Guest editorial: Ethics and privacy in learning analytics." Journal of Learning Analytics 3.1 (2016): 5-15.So is it worth it? Benefits of learning analyticsG. GrayBring understanding to learning and teaching practices. Disruptive innovation to improve the quality of the student learning experience 1. Scalable2. Inclusive3.PersonalisableGetting started…The data we collect currently: Generally: Exam grades Logs from centrally resourced technologies Library accesses Enrollment data From collaborative software Interactions Social networksThe latent constructs we want to measure: Improvement in the learningexperience Improvement in the quality of learning Effective learning disposition: persistence; self-regulation; deep learning; creativity; . . . . Affective state: boredom, engagement How do we get from DATA…….                  to INFORMATION ?What do we COUNT? What can we INFER from COUNTS?What evidence does the data provideHow do we get from the INFORMATION we want, to the DATA we need to collect?What could we count?  Back to the street light effect . . .How do we translate counts into information, and for whom?Student facing analytics; staff facing analytics; both?G. Gray40Data ScienceSocial Network analysisWho is responsible for acting on the information suggested by learning analytics?How are the results used, and by whom?How is this resourced?G. Gray41In conclusion. . . .1) What are we trying to accomplish? 2) How will we know that a change is an improvement? 3) What change can we make that will result in improvement?Answering these deceptively simple questions is complex work, and central to that work is the role of measurement.Krumm et al (2016). Practical measurement and productive persistence: Strategies for using digital learning system data. Journal of Learning Analytics, 3(2), 116–138.ORLA project, NF: https://www.teachingandlearning.ie/orlaDALTAÍ project (Developing all Learners Through Analytics:  https://daltai-he.ie/Your turn . . . 1. What Data is useful….: What are legitimate purposes for the college to use student data? What kind of information would be useful for you in your professional development? What kind of information would be useful for you in improving the student experience?2. Policy Do your policies cover these uses?G. Gray43Your turn . . . 3. What training would be useful to enable you engage with student data?4. Do you have concerns about incorporating learning analytics into your job?5. How do you think staff should approach acting on output from learning analytics? Module level / programme levelG. Gray44

How Can I use Learning Analytics in my Teaching Practice

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How Can I use Learning Analytics in my Teaching Practice

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