The possibility of predicting learning performance using features of note taking activities and instructions in a blended learning environment

Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hideaki

doi:10.1186/s41239-017-0048-z

Cited by 16 publications

(5 citation statements)

References 18 publications

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“…Finally, the third category is learning habits, which is again a relevant factor in succeeding in higher education (Lammers et al, 2001;Nakayama et al, 2017;Selvig et al, 2015). Among these, the use of resources, mentioned in our study, is associated with academic achievement (Selvig et al, 2015).…”

Section: Which Data Can Help In Predicting Non-thriving?mentioning

confidence: 59%

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students

Hershkovitz

Ambrose

2022

Learning Analytics

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In this qualitative study (N=6), we explored insights of first-year students’ instructors and advisors into an early identification system aimed at detecting non-thriving students in the context of an all-campus first-year orientation course for undergraduates. Following the development of that prediction model in a bottom-up manner, using a plethora of available data, we focus on how its end-users could help us understand the underlying mechanisms that drive the identification of non-thriving students. As findings suggest, participants were appreciative overall of the prediction and its timing and came up with various behaviours that could explain non-thriving, mostly motivation and engagement. They suggested additional data that could predict non-thriving, including background information, academic engagement, and learning habits.

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Section: Which Data Can Help In Predicting Non-thriving?mentioning

confidence: 59%

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students

Hershkovitz

Ambrose

2022

Learning Analytics

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“…The research found that the characteristics and backgrounds of some students and the designed features 88 http://www.i-jet.org can determine the learning results of students in BLE at a statically significant level. Nakayama, Mutsuura, and Yamamoto [12] studied the learning ability and learning attitude of students by writing a journal on BLE. The researchers analyzed the contents of the journals to estimate the scores from the final exam and to develop the learning ability of higher education students in Japan.…”

Section: Blended Learning Environmentmentioning

confidence: 99%

“…Porter, Kleve and Palermo [7] emphasized the use of technology in enhancing creative thinking skill. Much research also studied the learning achievement results of technology skills and positive attitudes toward learning through use of the e-portfolio and BLE [4] [5][8] [9][10] [11] [12] [13].…”

Section: Introductionmentioning

confidence: 99%

Students’ Beliefs Regarding the Use of E-portfolio to Enhance Cognitive Skills in a Blended Learning Environment

Koraneekij

Khlaisang

2019

Int. J. Emerg. Technol. Learn.

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This paper reports on a quantitative study on ICT readiness among undergraduate students in Thailand, students’ beliefs about use of e-portfolios in the Blended Learning Environment (BLE), and students’ beliefs about using e-portfolios to enhance their cognitive skills in the BLE. The sample group comprised 360 undergraduate students, divided by study fields. The data collection tool was a questionnaire of students’ beliefs. The reliability value of the questionnaire was 0.889. Data was analyzed using statistical analysis and f-test. The beliefs and needs were ranked by PNI modified. The research found that every student had a computer connected to the Internet. The analysis results of students’ beliefs about the use of e-portfolios in the BLE were positive and the top five results were: (1) learning by creating work, (2) enhancing creativity, (3) enhancing the problem solving skill, (4) enhancing critical thinking, and (5) enhancing authentic assessment. The current state of using e-portfolios to enhance cognitive skills in the BLE was at average level, while the needs were at the high level.

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“…The features of the number of terms extracted, the course sessions and the content assessments of notes taken were previously summarized in Figure 1 (Nakayama et al 2011(Nakayama et al , 2012. In the figure, the overall number of terms in notes was compared between lecturer and students across course sessions.…”

Section: Text Analysis Of Notes Takenmentioning

confidence: 99%

Note-Taking Evaluation using Network Illustrations based on Term Co-Occurrence in a Blended Learning Environment

Nakayama

Mutsuura

Yamamoto

2016

International Journal of Distance Education Technologies

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Note contents taken by students during a blended learning course were evaluated, to improve the quality of university instruction. To conduct a quantitative comparison of the contents of all notes for effective instruction from lecturer to students to occur, the contents were mathematically compared and evaluated using two ways of summarizing the frequency of term co-occurrences. In order to evaluate visually the differences between the contents of notes taken, an adjacency matrix and Levenshtein distance metrics were employed to represent noun co-occurrence in the notes. In comparing notes between the lecturer and students, insufficient distance and additional distance are defined and measured for all participants during the course. In the results, students recorded additional nouns to replace the nouns given by the lecturer, and introduced new nouns of their own as substitutes as well. There are significant correlation relationships between the above mentioned distances and the ratios, such as between the word ratio and coverage, which have been defined in previous studies. Also, summarizing ways of co-occurrence frequency did not affect any of the relationships. Finally, possible applications for visualizing learning activities of the lecturer and students are discussed.

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The possibility of predicting learning performance using features of note taking activities and instructions in a blended learning environment

Cited by 16 publications

References 18 publications

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students

Insights of Instructors and Advisors into an Early Prediction Model for Non-Thriving Students

Students’ Beliefs Regarding the Use of E-portfolio to Enhance Cognitive Skills in a Blended Learning Environment

Note-Taking Evaluation using Network Illustrations based on Term Co-Occurrence in a Blended Learning Environment

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