Learning Analytics

Introduction

Learner Analytics in my milieu is the gathering and analysis of my students’ data to make daily decisions in my pedagogical practices. My school has a student learning management system that captures all data learners generate during their interactions with online and offline learning environments. It helps me to optimize students’ learning and leverage decision-making related to learning, teaching, and educational management. The methods used are information gathered from the Student Learning Management System, Lesson Observation Plan, Students’ Survey, Students’ Informal Feedback, Teaching Reflection, and Intervention Report. There are four elements of learning analytics: data collected, student and classroom administration, learning environment, and learning management systems. The standard data sources are students’ log records, student characteristics, prior learning background, and academic performance. Although data enable Learning analytics, it is not driven by data. I typically leverage my decisions about my learners and how they should benefit my learners in an inclusive and diverse classroom. I used this information to identify learning difficulties and opportunities for learning support and improvement to the curriculum design (Shum & Crick, 2016, p. 8).

Learning Analytics tools adopted in my milieu

One of the tools I used in developing my curriculum for my photography CCA (core curricular activity) was to use an open resource called “Learning Designer”. The Learning Designer was developed by Dr Diana Laurillard and her team at the University City of London (UCL) and is available for use by any educator. The Learning Designer helps teachers and educators design teaching and learning activities using six learning types from the Conversational Framework. The framework includes a drop-down list of six learning types that best describes each activity you create: Is it learning from acquisition (Read/Watch/Listen)? Learning from inquiry? Learning from practice? Learning from production? Learning from the discussion? Or learning from collaboration? (Laurillard, Kennedy, Charlton, Wild, & Dimakopoulos, 2018).

The other tool I used was the Biological Science Curriculum Study (BSCS 5E model), which promotes a learning environment for collaborative learning. It involves steps to engage students with questions and curiosity; get students to explore without any direct instruction, leaving students to gather data to make predictions; encourage learners to explain what they have learned and introduce new terms and ideas; get students to elaborate their new ideas by applying new knowledge to practice; and get the student to evaluate by assessing all options and new ideas they have the practice to make the best choices (Gopal, 2009, pp. 21-22).

Benefits and Considerations

Learning Analytics helps provide insights into my learner's learning progress. Hence, I will be able to craft learning strategies that accommodate and modify learning tasks or activities. The critical user's ability to interpret data and turn it into meaningful action depends on the efficacy of the learning analytics tools that are appropriately used for intervention to improve student's progress in learning. Careful consideration of ethical and privacy issues associated with using personal data must be safeguarded and secured in the interest of students and the Institution. Ultimately, the benefit of any learning analytics is that it seeks to explore the optimal pathway to learning. Although it does not account for everything about the learners, it gives me some valuable information about my learners and their learning activities and progress to make responsive interventions. The intervention relating to planning, attention, simultaneous and successive (PASS) processing theory of intelligence could be operationalized with the Cognitive Assessment System – for better treatment of students with disabilities (Ruumol, Thangarajathi, & Ananthasayanam, 2011, p. 32).

Conclusions

In essence, learner analytics empowers learners by enhancing their control of learning decisions to develop self-regulated skills. It also helps improve teaching efficacy and efficiency by prompting critical reflections and actions among teachers based on student feedback. Moreover, learner analytics should inform teachers and administrators to make sound decisions to ensure a good teaching and learning environment. Learner Analytics is about managing learning, teaching, and educational environment. In summary, Learner Analytics is about closing a feedback loop that is enabled by data generated by learners and serves the purpose of enriching and enhancing learning and informing decisions in our educational practices (Wen & Song, 2021, p. 2).

References

Gopal, T. (August, 2009). Integration of the BSCS 5E Instructional Method and Technology in an Anatomy and Physiology Lab. Dissertation, University of Southern Mississippi , 1-57. Retrieved 8 August, 2021, from https://aquila.usm.edu/cgi/viewcontent.cgi?referer=https://scholar.google.com/&httpsredir=1&article=2086&context=dissertations

Laurillard, D., Kennedy, E., Charlton, P., Wild, J., & Dimakopoulos, D. (2018). Using technology to develop teachers as designers of TEL: Evaluating the learning designer. British Journal of Educational Technology, 49(6), 1044-1058. Retrieved 8 August, 2021, from https://bera-journals.onlinelibrary.wiley.com/doi/pdfdirect/10.1111/bjet.12697

Ruumol, K., Thangarajathi, S., & Ananthasayanam, R. (2011). Factor analytic study of cognitive processing and self-perception of learning disabilities among the elementary inclusive school children. Journal of Educational Psychology, 5(1), 32-38. Retrieved 7 August, 2021, from https://files.eric.ed.gov/fulltext/EJ1102286.pdf

Shum, S. B., & Crick, R. D. (2016). Learning analytics for 21st-century competencies. Journal of Learning Analytics, 3(2), 6-21. Retrieved 7 August, 2021, from https://files.eric.ed.gov/fulltext/EJ1126768.pdf

Wen, Y., & Song, Y. (2021). Learning Analytics for Collaborative Language Learning in Classrooms: From the Holistic Perspective of Learning Analytics, Learning Design and Teacher Inquiry. Educational Technology & Society, 24(1), 1-15.