Improving undergraduate student achievement in large blended courses through data-driven interventions

Dodge, Bernie; Whitmer, John C.; Frazee, James P.

doi:10.1145/2723576.2723657

Cited by 17 publications

(14 citation statements)

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“…Interventions through e-mails were shown to be the best treatment within constraints, while having an impact on student achievement Dodge et al (2015) University of Adelaide…”

Section: Arnold and Pistilli (2012) San Diego State Universitymentioning

confidence: 99%

Learning analytics in higher education: an analysis of case studies

Wong

2017

AAOUJ

109

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Purpose-The purpose of this paper is to present a systematic review of the mounting research work on learning analytics. Design/methodology/approach-This study collects and summarizes information on the use of learning analytics. It identifies how learning analytics has been used in the higher education sector, and the expected benefits for higher education institutions. Empirical research and case studies on learning analytics were collected, and the details of the studies were categorized, including their objectives, approaches, and major outcomes. Findings-The results show the benefits of learning analytics, which help institutions to utilize available data effectively in decision making. Learning analytics can facilitate evaluation of the effectiveness of pedagogies and instructional designs for improvement, and help to monitor closely students' learning and persistence, predict students' performance, detect undesirable learning behaviours and emotional states, and identify students at risk, for taking prompt follow-up action and providing proper assistance to students. It can also provide students with insightful data about their learning characteristics and patterns, which can make their learning experiences more personal and engaging, and promote their reflection and improvement. Originality/value-Despite being increasingly adopted in higher education, the existing literature on learning analytics has focussed mainly on conventional face-to-face institutions, and has yet to adequately address the context of open and distance education. The findings of this study enable educational organizations and academics, especially those in open and distance institutions, to keep abreast of this emerging field and have a foundation for further exploration of this area.

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“…Interventions through e-mails were shown to be the best treatment within constraints, while having an impact on student achievement Dodge et al (2015) University of Adelaide…”

Section: Arnold and Pistilli (2012) San Diego State Universitymentioning

confidence: 99%

Learning analytics in higher education: an analysis of case studies

Wong

2017

AAOUJ

109

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“…In the literature, course achievements have been widely studied from various perspectives [6], [7], [19]- [27]. Dodge et al [6] proposed to identify students at-risk of failing in two high enrollment courses by means of learning analytics methods.…”

Section: B Course Achievementmentioning

confidence: 99%

“…In the literature of computer assisted education or educational data mining [4], some efforts have been made in analyzing course selection [1], [5], analyzing course achievements [6], [7] and developing recommendation based system for personalized learning [8]- [10]. However, to our best knowledge, there is still a lack of work on optional course recommendation based on score prediction.…”

Section: Introductionmentioning

confidence: 99%

A Score Prediction Approach for Optional Course Recommendation via Cross-User-Domain Collaborative Filtering

et al. 2019

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Optional course selection is a critical activity for college students due to a large number of available but unfamiliar optional courses. Improper selection of optional courses would seriously affect the students' optional course achievements, which enforces students to drop out the improperly selected optional courses. Therefore, there is an urgent need to develop an optional course recommendation system. In this paper, we develop an optional course recommendation system based on score prediction. In particular, a novel cross-user-domain collaborative filtering algorithm is designed to accurately predict the score of the optional course for each student by using the course score distribution of the most similar senior students. After generating the predicted scores of all optional courses, the top t optional courses with the highest predicted scores without time conflict will be recommended to the student. The extensive experiments have been conducted to evaluate the effectiveness of the proposed method, and the results show that the proposed method is able to accurately recommend optional courses to students who will achieve relatively high scores. INDEX TERMS Optional course recommendation, score prediction, collaborative filtering, personalized learning.

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“…Dalam kegiatan belajar, terjadi pergeseran dari pembelajaran berpusat pada pengajar ke pembelajaran berpusat pada pemelajar (Senffner & Kepler, 2015). Keterlibatan pemelajar di dalam aktivitas belajar mencakup membaca, menulis, berbicara berpikir, berdebat, melakukan kerja kelompok, dan melakukan peragaan hasil kegiatan belajar (Dodge, Whitmer, & Frazee, 2015).…”

Section: Prinsip-prinsip Blended Learningunclassified

“…Ditegaskan olehSenffner & Kepler (2015),Keengwe & Agamba (2015), danDodge, Whitmer, & Frazee (2015), pelaksanaan pembelajaran blended learning merupakan hasil dari pertimbangan seksama perancangan pembelajaran untuk memberikan pengalaman belajar terbaik baik pemelajar. Blended learning jelas merupakan hasil dari suatu proses panjang perancangan kegiatan instruksional.Untuk menghasilkan blended learning yang berkualitas baik, salah satu model perancangan kegiatan instruksional yang dapat digunakan adalah model ADDIE yang dipopulerkan olehDick dan Carey (1990).…”

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Rancangan Model Pembelajar Blended Learning Pada Program Pendidikan Bahasa Inggris Di Universitas Timor Indonesia

Lasi

2018

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Blended learning dianggap sebagai model pembelajaran yang tepat untuk diterapkan di Unimor karena dalam pelaksanaannya memungkinkan adanya perpaduan antara pertemuan tatap muka di kelas dengan komponenkomponen pembelajaran daring. Penggunaan berbagai teknologi daring juga diidentifikasi dengan memperhatikan kebutuhan pemelajar untuk mengembangkan keterampilan sesuai keahlian di bidangnya. Pelaksanaan blended learning dapat mendukung mahasiswa untuk memperoleh kualitas hasil belajar yang lebih baik. Kajian konseptual mengenai pengembangan mata kuliah blended learning ini dimulai dengan memaparkan prinsip-prinsip blended learning yang dapat diterapkan di Unimor, kemudian dilanjutkan dengan identifikasi manfaat pelaksanaannya pada mata kuliah Bahasa Inggris. Rancangan konseptual pada tulisan ini selanjutnya akan digunakan sebagai landasan teori untuk mendukung penelitian pengembangan mata kuliah blended learning Percakapan dan Mendengarkan Bahasa Inggris di Unimor.

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Improving undergraduate student achievement in large blended courses through data-driven interventions

Cited by 17 publications

References 0 publications

Learning analytics in higher education: an analysis of case studies

Learning analytics in higher education: an analysis of case studies

A Score Prediction Approach for Optional Course Recommendation via Cross-User-Domain Collaborative Filtering

Rancangan Model Pembelajar Blended Learning Pada Program Pendidikan Bahasa Inggris Di Universitas Timor Indonesia

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