Guido Makransky

Experimental and Cognitive Psychology · 2007–2022

A researcher in the Science corpus: 10 papers; trusts 45 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Experimental and Cognitive Psychology — 59 citations into it; #2,769 of 9,731 by trust here, #2,785 by citations
• Human-Computer Interaction — 59 citations into it; #586 of 2,253 by trust here, #416 by citations
• Education — 54 citations into it
• Social Psychology — 50 citations into it
• Developmental and Educational Psychology — 46 citations into it; #3,045 of 8,223 by trust here, #1,995 by citations
• Management Science and Operations Research — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it; #19,797 of 21,575 by trust here, #18,266 by citations
• Automotive Engineering — 13 citations into it

Whom Guido Makransky trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard E. Mayer
2. Roxana Moreno
3. Elinda Ai-Lim Lee
4. Reinhard Pekrun
5. K. Wong
6. Fred D. Davis
7. Everett V. Smith
8. K. Ann Renninger
9. Logan Fiorella
10. Timothy A. Brown

Who trusts Guido Makransky overall

1. Oliver A. Meyer
2. Magnus K. Omdahl
3. Niels Koch Andreasen
4. Richard E. Mayer
5. Sarune Baceviciute
6. Alexander Skulmowski
7. Jocelyn Parong
8. Mina C. Johnson-Glenberg
9. Patrick Albus
10. Lau Lilleholt

Papers from Guido Makransky's perspective

Ordered by how strongly the researchers Guido Makransky trusts endorse each paper. Same corpus, a different order for every researcher.

1. Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. (American Psychologist)
2. Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions.
3. Interactive Multimodal Learning Environments
4. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology
5. Situational and individual interest.
6. The Power of Interest for Motivation and Engagement
7. The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries, and Implications for Educational Research and Practice
8. Achievement Emotions: A Control-Value Approach
9. Computer Gaming and Interactive Simulations for Learning: A Meta-Analysis
10. A Social-Cognitive, Control-Value Theory of Achievement Emotions

Their papers

• A study of how immersion and interactivity drive VR learning (2022) — 316 citations
• Immersive virtual reality increases liking but not learning with a science simulation and generative learning strategies promote learning in immersive virtual reality. (2020) — 314 citations
• Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) — 411 citations
• Motivational and cognitive benefits of training in immersive virtual reality based on multiple assessments (2019) — 428 citations
• A structural equation modeling investigation of the emotional value of immersive virtual reality in education (2018) — 674 citations
• Development and validation of the Multimodal Presence Scale for virtual reality environments: A confirmatory factor analysis and item response theory approach (2017) — 353 citations
• Adding immersive virtual reality to a science lab simulation causes more presence but less learning (2017) — 1,282 citations
• Critical Values for Yen’s Q3: Identification of Local Dependence in the Rasch Model Using Residual Correlations (2017) — 613 citations
• Early productive vocabulary predicts academic achievement 10 years later (2016) — 188 citations
• Testing Vocational Interests and Personality as Predictors of Person-Vocation and Person-Job Fit (2007) — 90 citations