Glenn Lopez
Impact in
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- Online Learning and Analytics
- E-Learning and Knowledge Management
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- Innovative Teaching and Learning Methods
Papers in
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- Online Learning and Analytics 9
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- Intelligent Tutoring Systems and Adaptive Learning 3
- Imbalanced Data Classification Techniques 2
- Data Stream Mining Techniques 2
- Machine Learning and Data Classification 1
- Co-authors
- Justin Reich (6 shared papers)Jacob Whitehill (6 shared papers)Cody Coleman (5 shared papers)Joseph Jay Williams (4 shared papers)Isaac L. Chuang (3 shared papers)Andrew Ho (2 shared papers)Curtis G. Northcutt (2 shared papers)Rebecca P. Petersen (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (1 paper)SSRN Electronic Journal (2 papers)DSpace@MIT (Massachusetts Institute of Technology) (2 papers)Educational Data Mining (2 papers)
- Partner nations
- United StatesSingaporeAustralia
In The Last Decade
Glenn Lopez
10 papers receiving 397 citations
Peers
Comparison fields: 5 of 64
- Computer Science Applications 319
- Developmental and Educational Psychology 65
- Education 136
- Artificial Intelligence 101
- Information Systems 60
Countries citing papers authored by Glenn Lopez
This map shows the geographic impact of Glenn Lopez's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Glenn Lopez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glenn Lopez more than expected).
Fields of papers citing papers by Glenn Lopez
This network shows the impact of papers produced by Glenn Lopez. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Glenn Lopez. The network helps show where Glenn Lopez may publish in the future.
Co-authors
The 19 scholars most cited alongside Glenn Lopez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 166 | |
| 2 | 2020 | 104 | |
| 3 | 2015 | 58 | |
| 4 | 2018 | 20 | |
| 5 | HarvardX and MITx: Two Years of Open Online Courses Fall 2012-Summer 2014 | 2015 | 19 |
| 6 | 2017 | 18 | |
| 7 | Beyond Prediction: First Steps toward Automatic Intervention in MOOC Student Stopout. | 2015 | 14 |
| 8 | 2017 | 9 | |
| 9 | Adaptive Assessment Experiment in a HarvardX MOOC. | 2017 | 4 |
| 10 | Beyond Prediction: Towards Automatic Intervention in MOOC Student Stop-out. | 2015 | 3 |
| 11 | 2016 | 1 |
About Glenn Lopez
Glenn Lopez is a scholar working on Computer Science Applications, Artificial Intelligence, Clinical Psychology, Literature and Literary Theory and Media Technology, having authored 11 papers that have together received 416 indexed citations. Recurring topics across this work include Online Learning and Analytics (9 papers), Intelligent Tutoring Systems and Adaptive Learning (3 papers), Imbalanced Data Classification Techniques (2 papers), Data Stream Mining Techniques (2 papers), Behavioral Health and Interventions (1 paper), Experimental Learning in Engineering (1 paper), Machine Learning and Data Classification (1 paper) and Second Language Learning and Teaching (1 paper). The work is most often cited by research in Computer Science Applications (319 citations), Developmental and Educational Psychology (65 citations), Education (136 citations), Artificial Intelligence (101 citations) and Information Systems (60 citations). Glenn Lopez has collaborated with scholars based in United States, Singapore and Australia. Frequent co-authors include Justin Reich, Jacob Whitehill, Cody Coleman, Joseph Jay Williams, Isaac L. Chuang, Andrew Ho, Curtis G. Northcutt, Rebecca P. Petersen, Dustin Tingley and J. E. D. Williams. Their work appears in journals such as Proceedings of the National Academy of Sciences, SSRN Electronic Journal, DSpace@MIT (Massachusetts Institute of Technology) and Educational Data Mining.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.