Julie Hardman
- Computer Science Applications top 1%
- Artificial Intelligence top 10%
- Education top 10%
- Information Systems top 10%
- Management Information Systems top 10%
- Co-authors
- Naif Radi AljohaniRaheel NawazSaeed‐Ul HassanHajra WaheedSalem AlelyaniSai NudurupatiAlberto Paucar‐CaceresCathy Urquhart
- Topics
- Online Learning and Analytics (4 papers)Knowledge Management and Sharing (2 papers)Big Data and Business Intelligence (2 papers)
- Journals
- Computers in Human BehaviorJournal of the Association for Information SystemsProduction Planning & Control
- Partner nations
- United KingdomNew ZealandIndia
In The Last Decade
Julie Hardman
8 papers receiving 505 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Science Applications 279
- Artificial Intelligence 137
- Education 98
- Information Systems 94
- Management Information Systems 81
Countries citing papers authored by Julie Hardman
This map shows the geographic impact of Julie Hardman'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 Julie Hardman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julie Hardman more than expected).
Fields of papers citing papers by Julie Hardman
This network shows the impact of papers produced by Julie Hardman. 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 Julie Hardman. The network helps show where Julie Hardman may publish in the future.
Co-authorship network of co-authors of Julie Hardman
This figure shows the co-authorship network connecting the top 25 collaborators of Julie Hardman. A scholar is included among the top collaborators of Julie Hardman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Julie Hardman. Julie Hardman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | Predicting academic performance of students from VLE big data using deep learning modelsbreakdown → | 337 |
| 3 | The Impact of Data Analytics on Decision Making Processes and Firm Performance | 1 |
| 4 | 81 | |
| 5 | 29 | |
| 6 | 45 | |
| 7 | Predicting Students Progression Using Existing University Datasets: A Random Forest Application | 1 |
| 8 | Tapping the Educational Potential of Facebook: Leveraging Social Capital and Knowledge | 1 |
| 9 | 16 |
About Julie Hardman
Julie Hardman is a scholar working on Computer Science Applications, Management Information Systems and Communication, having authored 9 papers that have together received 530 indexed citations. Recurring topics across this work include Online Learning and Analytics (4 papers), Knowledge Management and Sharing (2 papers) and Big Data and Business Intelligence (2 papers). The work is most often cited by research in Computer Science Applications (279 citations), Health Information Management (47 citations) and Management Information Systems (81 citations). Julie Hardman has collaborated with scholars based in United Kingdom, New Zealand and India. Frequent co-authors include Naif Radi Aljohani, Raheel Nawaz, Saeed‐Ul Hassan, Hajra Waheed, Salem Alelyani, Sai Nudurupati, Alberto Paucar‐Caceres, Cathy Urquhart, Alan H. Fielding and Patrizia Garengo. Their work appears in journals such as Computers in Human Behavior, Journal of the Association for Information Systems and Production Planning & Control.
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.