Daniel Macher

20 papers receiving 1.0k citations

Daniel Macher's Hit Papers

Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction 2009 · 528 citations
5280+5+11Years since publication100200300400500

Peers

Daniel Macher
Comparison fields: 5 of 88
  • Computer Science Applications 185
  • Statistics and Probability 271
  • Education 655
  • Information Systems and Management 102
  • Developmental and Educational Psychology 150
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Jacqueline Bichsel United States
Menucha Birenbaum Israel
Joseph A. Rios United States
Julia H. Kaufman United States
Drew Polly United States
Sarah Hofer Germany
Jiun‐Yu Wu Taiwan
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Johannes Naumann Germany
Rohani Ahmad Tarmizi Malaysia
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Countries citing papers authored by Daniel Macher

Since Specialization
Citations

This map shows the geographic impact of Daniel Macher'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 Daniel Macher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Macher more than expected).

Fields of papers citing papers by Daniel Macher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Macher. 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 Daniel Macher. The network helps show where Daniel Macher may publish in the future.

Co-authors

The 24 scholars most cited alongside Daniel Macher, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Macher Line = papers co-authored together Daniel Macher links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction
Hit paper breakdown →
2009528
2 2011172
3 2012108
4 201799
5 201163
6 201545
7 201529
8 201725
9 202215
10 202211
11 20219
12 20168
13 20236
14 20106
15 20104
16 20213
17 20133
18 20242
19 20141
20 20151

About Daniel Macher

Daniel Macher is a scholar working on Education, Sociology and Political Science, Experimental and Cognitive Psychology, Statistics and Probability and Social Psychology, having authored 22 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistics Education and Methodologies (5 papers), School Choice and Performance (4 papers), Education, Achievement, and Giftedness (4 papers), Sociology and Education Studies (4 papers), Education Methods and Technologies (3 papers), Motivation and Self-Concept in Sports (3 papers), Innovations in Educational Methods (3 papers) and Communication in Education and Healthcare (3 papers). The work is most often cited by research in Computer Science Applications (185 citations), Statistics and Probability (271 citations), Education (655 citations), Information Systems and Management (102 citations) and Developmental and Educational Psychology (150 citations). Daniel Macher has collaborated with scholars based in Austria, United Kingdom and United States. Frequent co-authors include Manuela Paechter, Brigitte Maier, Ilona Papousek, Kai Ruggeri, H. Harald Freudenthaler, Sigrid Wimmer, Khatuna Martskvishvili, Martin Arendasy, Elisabeth M. Weiss and Silke Luttenberger. Their work appears in journals such as Frontiers in Psychology, Journal of Personality Assessment, Computers & Education, Research in Science Education and Education and Information Technologies.

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.

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