Predictors of study success in the reviewed studies draw on two broad data sets: online behaviour trace data and students' background information¶

Claim · All claims
Evidence · 1 study (2 entries) · review r2–r3 · q2
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? One set of predictors is based on online behaviour data such as forum interactions, engagement with learning artefacts and logfiles; another set is based on demographics, socio-economic status and prior academic performance. → Dirk Ifenthaler 2020 q2 i? Background predictors include demographics, socio-economic status, prior academic experience and performance, and survey self-reports such as expected grades and motivation. → Dirk Ifenthaler 2020 (2)

Evidence¶

Dirk Ifenthaler 2020¶

Dirk Ifenthaler, Jane Yin-Kim Yau. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Education Tech Research Dev. https://doi.org/10.1007/s11423-020-09788-z

q2 · i? · review · r2

Synthesis of the predictors reported in the 46 key publications (Table 1). The review reports that "One set of predictors is based on data collected through online behaviour, mainly logfiles and trace-data", including forum interactions and engagement with learning artefacts.

"One set of predictors is based on data collected through online behaviour, mainly logfiles and trace-data. This includes forum interactions (e.g., posts, replies, length of posts)"

Dirk Ifenthaler 2020 (2)¶

Dirk Ifenthaler, Jane Yin-Kim Yau. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Education Tech Research Dev. https://doi.org/10.1007/s11423-020-09788-z

q2 · i? · review · r3

Synthesis of background-variable predictors across the key publications, citing studies using enrolment age, scholarships, GPA, financial background and academic history. The review also notes survey-based predictors such as self-reported expected grades and motivation.

"another set of data used for predicting study success is based on students' background information, such as demographics (e.g., age, gender), socio-economic status (e.g., family income, background, expenditure), prior academic experience and performance"

Discussion¶

Related Claims¶

• In association-rule mining of survey data from 530 college students in online courses, goal setting, environment structuring and time management were the strategies most often associated with lower digital distraction — related
• None of the 46 key publications on learning analytics for study success were rated as strong research rigour (11 weak; 35 moderate) — related