What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Cognitive psychology
- The Internet
Peter Gerjets mostly deals with Cognitive load, Cognitive psychology, Eye tracking, Instructional design and Human–computer interaction.
He has researched Cognitive load in several fields, including Educational psychology, Secondary task, Mental load and Artificial intelligence.
His Eye tracking research is multidisciplinary, relying on both The Internet and Eye movement.
His studies in Instructional design integrate themes in fields like Hypertext and Learning sciences.
Peter Gerjets has included themes like Control, Teaching method and Multimedia in his Human–computer interaction study.
His Multimedia study incorporates themes from Protocol analysis and Rendering.
His most cited work include:
- In the eyes of the beholder: How experts and novices interpret dynamic stimuli (256 citations)
- Learner Control in Hypermedia Environments (236 citations)
- Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? (223 citations)
What are the main themes of his work throughout his whole career to date?
Peter Gerjets spends much of his time researching Multimedia, Cognitive psychology, Artificial intelligence, Human–computer interaction and Cognitive load.
His study in the field of Hypermedia also crosses realms of Engineering.
His research integrates issues of Communication, Working memory, Visual perception, Eye movement and Instructional design in his study of Cognitive psychology.
Peter Gerjets focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Machine learning and, in some cases, Set.
His work in Human–computer interaction covers topics such as Visualization which are related to areas like Spatial ability, Mental image and Motion.
The various areas that Peter Gerjets examines in his Cognitive load study include Mental effort, Mental load and Educational psychology.
He most often published in these fields:
- Multimedia (28.70%)
- Cognitive psychology (26.09%)
- Artificial intelligence (20.87%)
What were the highlights of his more recent work (between 2014-2021)?
- Working memory (13.91%)
- Cognitive psychology (26.09%)
- Artificial intelligence (20.87%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Working memory, Cognitive psychology, Artificial intelligence, Executive functions and Machine learning.
His work on Short-term memory as part of his general Working memory study is frequently connected to Predictive value, thereby bridging the divide between different branches of science.
His research links Hypermedia with Cognitive psychology.
His Mathematics education research extends to Artificial intelligence, which is thematically connected.
Peter Gerjets interconnects Learning environment, Range and Set in the investigation of issues within Machine learning.
His work in Eye tracking addresses subjects such as Active learning, which are connected to disciplines such as Human–computer interaction.
Between 2014 and 2021, his most popular works were:
- When flanker meets the n-back: What EEG and pupil dilation data reveal about the interplay between the two central-executive working memory functions inhibition and updating (55 citations)
- Pupil Dilation and EEG Alpha Frequency Band Power Reveal Load on Executive Functions for Link-Selection Processes during Text Reading (48 citations)
- When adults without university education search the Internet for health information (47 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Cognitive psychology
- Cognitive science
Peter Gerjets mainly investigates Pupillometry, Executive functions, Working memory, Pupillary response and Artificial intelligence.
His Pupillometry research incorporates a variety of disciplines, including Cognitive psychology, n-back, Inhibitory control, Eye tracking and Similarity.
Peter Gerjets has researched Executive functions in several fields, including Young adult, Speech recognition and Perception.
His Artificial intelligence research incorporates elements of Cognitive load, Machine learning and Set.
His research in Machine learning intersects with topics in Learning environment, Range and Adaptation.
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