Necessary conditions of learning

Reeves, Philip M.; Sperling, Rayne A.; Follmer, D. Jake; Pun, Wik Hung; Oeder, Christa E.; Towle, Alexander L.

doi:10.1080/00220671.2015.1092729

Cited by 2 publications

(2 citation statements)

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“…Despite the wide use of learning analytics in addressing the above-mentioned challenges in education and the results it has produced, researchers have pointed out that only a limited number of learning analytics studies take into account theoretically established educational theories, with the majority of the published work primarily taking empirical approaches to research design (Boyd & Crawford, 2012). This has limited its potential to produce insightful ideas of students' intentions underlying their behaviours and strategies and to precisely locate problems in learning, as well as generate actionable knowledge to enhance student experiences and learning outcomes (Long & Siemens, 2011). To improve the insights, learning analytics research should be well grounded in educational theories and employ complementary methods, such as self-report.…”

Section: Learning Analytics Researchmentioning

confidence: 99%

Combining self-reported and observational measures to assess university student academic performance in blended course designs

Han

Ellis

2020

AJET

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This study combined the methods from student approaches to learning and learning analytics research by using both self-reported and observational measures to examine the student learning experience. It investigated the extent to which reported approaches and perceptions and observed online interactions are related to each other and how they contribute to variation in academic performance in a blended course design. Correlation analyses showed significant pairwise associations between approaches and frequency of the online interaction. A cluster analysis identified two groupings of students with different reported learning orientations. Based on the reported learning orientations, one-way ANOVAs showed that students with understanding orientation reported deep approaches to and positive perceptions of learning. The students with understanding orientation also interacted more frequently with the online learning tasks and had higher marks than those with reproducing orientation, who reported surface approaches and negative perceptions. Regression analyses found that adding the observational measures increased 36% of the variance in the academic performance in comparison with using self-reported measures alone (6%). The findings suggest using the combined methods to explain students’ academic performance in blended course designs not only triangulates the results but also strengthens the acuity of the analysis. Implications for practice or policy: Using combined methods of measuring learning experience offers a relatively more comprehensive understanding of learning. Combining self-reported and observational measures to explain students’ academic performance not only enables the results to be triangulated but also strengthens the acuity of the analysis. To improve student learning in blended course design, teachers should use some strategies to move students from a reproducing learning orientation towards an understanding orientation and encourage active online participation by highlighting the importance of learning online.

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Section: Learning Analytics Researchmentioning

confidence: 99%

Combining self-reported and observational measures to assess university student academic performance in blended course designs

Han

Ellis

2020

AJET

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“…These may include individual study and independent achievement activities such as individual presentations, self-evaluations and, more recently, the flipped classroom (Jensen, Holt, Sowards, Ogden, & West, 2018). The third category includes the interactive learning environments created by educators who use groupbased modalities (e.g., Frey, Fisher, & Everlove, 2009), including cooperative learning in workshops (Johnson & Johnson, 2009) and collaborations on products such as group presentations (Marton, 2015).…”

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confidence: 99%

The Value of Pedagogical Preferences: A Case of Personality and Learning Environments in Higher Education

Davies

Wilson

2020

IJEP

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To improve learning outcomes, research evidence has accumulated regarding the principles of teaching and learning; however, students’ perceptions of teaching methods have received little scientific investigation toward enhanced quality of their learning. To provide a demonstration of the value of researching student perceptions of the learning environments in which they find themselves, a sample of preference ratings (n = 69) was examined to test the hypothesis there exist among the Five Factor personality dimensions correlates of preference ratings for three environments: teacher-led, independent-autonomous, and groups. Results confirmed preference for group learning in our sample and statistically reliable zero-order positive correlations between group-based learning preference and both extraversion and openness scores and between preference for teacher-led environments and openness scores. First-order correlations showed no significant changes in accounted preference variation when controlling the other personality factors scores. These findings are discussed with respect to likely social-cognitive and neurodevelopmental bases of group learning effectiveness and the utility of investigating student preferences for improving the quality of learning.

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Necessary conditions of learning

Cited by 2 publications

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Combining self-reported and observational measures to assess university student academic performance in blended course designs

Combining self-reported and observational measures to assess university student academic performance in blended course designs

The Value of Pedagogical Preferences: A Case of Personality and Learning Environments in Higher Education

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