Learning Analytics and the Scholarship of Teaching and Learning - an obvious connection - Deborah West - Charles Darwin University
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The document discusses the integration of learning analytics and the scholarship of teaching and learning (SoTL) to optimize educational practices. It outlines the SoTL process, academic demographics, and insights regarding faculty interests in utilizing data for teaching improvements. Key points emphasize the need for academic engagement in developing learning analytics frameworks to enhance teaching and student performance.
Learning Analytics and the Scholarship of Teaching and Learning - an obvious connection - Deborah West - Charles Darwin University
- 1. A/Professor Deborah West, Charles Darwin University Learning Analytics and the Scholarship of Teaching and Learning: an obvious connection
- 2. Learning Analytics ‘measurement, collection, analysis and reporting of data about learners and their contexts, for the purposes of understanding and optimising learning and the environments in which it occurs’ (Siemens & Long, 2011, p. 34) 2
- 3. Levels of Data Integration 1. Stand-alone LMS data 2. LMS data integrated with student information system data 3. Data Warehouse 3
- 4. What is SoTL? ‘The scholarship of teaching and learning is, at its core, an approach to teaching that is informed by inquiry and evidence (both one’s own, and that of others) about student learning’ (Hutchings, Huber & Ciccone, 2011, p. 3) “systematic reflection on teaching and learning made public.” (Illinois State University, 1998) 4
- 5. SoTL Process 1. Using a theory, model or framework to ground the initiative and provide justification of action. 2. Identify an intervention 3. Formulating an investigative question, which is essentially the hypothesis in research terms. 4. Conducting an investigation 5. Produce a result in the form of a public artefact 6. Inviting peer review/dissemination 5
- 6. Academic Survey Demographics 6 Variable Category Absolute Frequency Relative Frequency Location (n = 351) Australia 341 97% New Zealand 10 3% Primary Work Role (n = 353) Teaching Students 188 53% Learning Support 47 13% Management/Administration 37 11% Other 32 9% Research 24 7% Academic Development 18 5% Student Support 7 2% LMS at Institution (n = 353) Blackboard 203 58% Moodle 124 35% Brightspace (D2L) 13 4% Sakai 2 1% Other 11 3% Employment Basis (n = 351) Full Time 284 81% Part Time 44 13% Casual 18 5% Other 5 1% Academic Level (n = 351) Lecturer 124 35% Senior Lecturer 88 25% Other 59 17% Associate Professor 30 9% Associate Lecturer/Tutor 30 9% Professor 20 6% Length of employment in current institution (n = 324) Less than 1.5 years 40 12% 1.5 – 5 years 68 21% 5 – 10 years 96 30% 10- 20 years 86 27% More than 20 years 34 11% Length of employment in Higher Education Sector (n = 345) Less than 1.5 years 11 3% 1.5 – 5 years 42 12% 5 – 10 years 85 25% 10- 20 years 130 38% More than 20 years 77 22% Involvement in teaching students (n = 353) Teaches students 276 78% Does not teach students 77 22%
- 7. Learning analytics discussion frequency 7 From the Academic Level Survey Notes: n varies between 234 and 253 per group due to missing data
- 8. Learning analytics activity participation From the Academic Level Survey Notes: * denotes mutually exclusive response n = 276
- 9. Training activity and interests 9
- 10. Institutional ratings around learning analytics Notes: n varies between 230 and 232 per category due to missing data
- 11. Interest in Learning Analytics Applications Notes: n varies between 311 and 317 per category due to missing data Excludes those people who indicated ‘not sure’ (between 12 and 29 per category) to better illustrate trends visually.
- 12. What academic staff want “Tell me what data is available, give me access to it, give me the time to use it and give me guidance in using it”. 12
- 13. Course/Curriculum design & teaching improvement 13 Is course design effective? How can I improve my courses design and teaching to improve engagement and performance? Which courses are performing well (within a school, faculty, university)? What types of content are included in courses? Is there a correlation between different course ‘styles’ (e.g. instructivist vs constructivist) and student achievement? What tools/methods are more engaging? What do students value or neglect? What concepts are students struggling with the most? What are the learning activities that lead to better outcomes?
- 14. Improve retention and student performance Which students are most at risk? What are the indicators of risk? What effect does intervention with students have? What kind of follow up helps? What interventions are more likely to be effective? What trends can we see in terms of at risk students Are there relationships between progression, enrolment status and performance? 14
- 15. What does student behaviour mean? How active are students in course content overall and at an individual item level? How does the information related to engagement fit with student feedback? What is the best way to structure content to improve learning performance? What do students most value? Most like? Have they accessed recordings or specific tools (e.g. wikis, blogs, journals etc.) How does this correlate with what content the academic delivers? If my students are clicking on something a lot, does it mean: – They love it? – They don’t understand it? – They hate it and have to keep coming back because it is too difficult or unpalatable to manage? 15
- 16. Key interests of academics • Being able to better understand who is in their class (demographics, prior academic history etc.) • Being able to have consolidated information about their individual students at the touch of a button (e.g. seeing how their students are doing in other units, what their demographic data is, whether they are using resources etc. all in one place) • Learning analytics being used by people centrally to better justify or evidence directives relating to their teaching (e.g. when academics are told to respond in 24 hours to students is there evidence for this being useful?) • Improving BOTH student (e.g. resource access patterns, socialisation) and teacher (e.g. teaching style, unit design) behaviour with respect to learning 16
- 17. Key points SoTL can help us to develop our learning analytics frameworks around pedagogy and good teaching practice SoTL can provide the framework for using the data generated by the systems at a local level. To develop and use learning analytics to improve teaching and learning will require engagement from academics A SoTL focus may help to engage academics in the learning analytics journey – both in development and application 17
- 18. References Siemens, G. & Long, P. (2011) Penetrating the Fog: Analytics in learning and education. EDUCAUSE Review, 46(4) July/August. Retrieved from http://www.educause.edu/ero/article/penetrating-fog-analytics-learning-and- education Prosser & Trigwell (1999). Understanding learning and teaching: The experience in higher education. Open University Press, Maidenhead. Trigwell, K. (2012) ‘Scholarship of teaching and learning’ chpt. 15 in L. Hunt & D. Chalmers (Eds) University Teaching in Focus: A learning-centred approach. ACER Press and Routledge, Taylor & Francis Group. London. 18
- 19. Acknowledgement of Research Partners: Dr Henk Huijser, Dr Jurg Bronnimann, Professor Alf Lizzio, Professor Carol Miles, Mr Bill Searle, Mr Danny Toohey, Mr David Heath Acknowledgement of Graphics Ms Mel Macklin Acknowledgement of Funding: Australian Government: Office for Learning and Teaching Further information on the project can be found at: http://www.letstalklearninganalytics.edu.au/ 19