3-2-1 summary by Heather Ryan https://padlet.com/hryan4_1/1pnttaubk1xwmnan Learning analytics is a means to process big data necessitated by technological means. Results of the analysis provide valuable data that can be used to make actionable future decisions (Kurni, 2021, pp. 1-3). en-us 2024-05-28 18:42:37 UTC 2024-05-29 05:31:39 UTC hello@padlet.com https://padlet.net/icons/png/1f4a1.png hryan4_1 https://padlet.com/hryan4_1/1pnttaubk1xwmnan/wish/3010561950 2024-05-28 18:49:52 UTC https://padlet.com/hryan4_1/1pnttaubk1xwmnan/wish/3010561950 hryan4_1 https://padlet.com/hryan4_1/1pnttaubk1xwmnan/wish/3010572070 According to Kurni (2021), learning analytics provides benefits at 4 different stakeholder levels.

1) Mega- Governance level to direct policy making inter/intra organizational decisions(p. 13).

2)Macro- Institution level that informs decisions related to student retention and cohort development (p. 13). The importance of reviewing declining student enrollment in higher education is additonally echoed by Educause in 2021 (p. 20).

3) Meso- Teacher and facilitator level to support the creation of robust and valuable course material (Kurni, 2021, p. 13).

4) Micro- Student level that promotes higher performance in relation to curriculum (Kurni, 2021, p. 13)

]]> 2024-05-28 19:02:48 UTC https://padlet.com/hryan4_1/1pnttaubk1xwmnan/wish/3010572070 hryan4_1 https://padlet.com/hryan4_1/1pnttaubk1xwmnan/wish/3010575434 There are two ways that I anticipate using learning analytics. In a role with a charter school consultation, I could foresee the applicability at the macro level data results in shaping enrollment and successful cohort development. As an adjunct professor, I would be interested in findings from the meso-level, to further enhance my curriculum and adjust my practice as needed.

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