Vincent Hoogerheide
Biographic Data
| ID | 4609431 |
|---|---|
| NAME | Vincent Hoogerheide |
| GIVEN NAMES | Vincent |
| FAMILY NAME | Hoogerheide |
| SIGNATURE | HOOGERHEIDE V |
| AFFILIATIONS | Utrecht University |
| ORCID | 0000-0003-4176-0973 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Learning by explaining through digital devices
Recent meta-analytical evidence shows that learning by explaining through digital devices (e.g., computers or tablets) is effective, but also reveals substantial heterogeneity in effect sizes. The present study was designed to shed light on two theoretically plausible moderators of such learning by digital explaining: the modality of (oral) explaining (audio + visual vs. audio only) and learners' level of the personality trait of extraversion. We…
Combining non-interactive teaching and drawing fosters conceptual knowledge but not monitoring accuracy from guided inquiry in science learning
When is observing failure productive? Investigating the role of solution diversity in vicarious failure
Prior research has shown that Productive Failure (PF), where learners attempt (and fail) to solve a problem prior to receiving instruction, is more effective for conceptual knowledge acquisition than receiving instruction first (Direct Instruction; DI). Higher diversity in generated solution attempts seemed positively associated with conceptual knowledge acquisition. The present study investigated whether observing another student’s attempts to s…
Shifting online
Instructing students on effective sequences of examples and problems
Nowadays, students often practice problem‐solving skills in online learning environments with the help of examples and problems. This requires them to self‐regulate their learning. It is questionable how novices self‐regulate their learning from examples and problems and whether they need support. The present study investigated the open questions (1) to what extent students' (novices) task selections align with instructional design principles and…
How do higher education students regulate their learning with video modeling examples, worked examples, and practice problems
Presenting novices with examples and problems is an effective and efficient way to acquire new problem-solving skills. Nowadays, examples and problems are increasingly presented in computer-based learning environments, in which learners often have to self-regulate their learning (i.e., choose what type of task to work on and when). Yet, it is questionable how novices self-regulate their learning from examples and problems, and to what extent thei…
A change of scenery
Two experiments investigated the effects of an instructional video's setting on learners' retention and application of the video content. Experiment 1 explored competing hypotheses based on theoretical assumptions about whether an authentic setting would serve as a distraction or as a cue for the instructor's expertise. Participants (N = 59) watched a video about floral diagrams and floral formulas that was either shot in a greenhouse (authentic …
Timing matters! Explaining between study phases enhances students’ learning
Previous research has shown that explaining is an effective activity to enhance learning.In prior studies, students were instructed to explain the contents after completing an entire learning phase.Explaining at the end of a learning phase, however, may be less apt to support comprehension monitoring and subsequent regulation activities.In two experiments, we investigated whether explaining in earlier phases of studying (i.e., in-between explaini…
When is observing failure productive? Investigating the role of solution diversity in vicarious failure
Prior research has shown that Productive Failure (PF), where learners attempt (and fail) to solve a problem prior to receiving instruction, is more effective for conceptual knowledge acquisition than receiving instruction first (Direct Instruction; DI). Higher diversity in generated solution attempts seemed positively associated with conceptual knowledge acquisition. The present study investigated whether observing another student’s attempts to s…
A change of scenery
Two experiments investigated the effects of an instructional video's setting on learners' retention and application of the video content. Experiment 1 explored competing hypotheses based on theoretical assumptions about whether an authentic setting would serve as a distraction or as a cue for the instructor's expertise. Participants (N = 59) watched a video about floral diagrams and floral formulas that was either shot in a greenhouse (authentic …
Timing matters! Explaining between study phases enhances students’ learning
Previous research has shown that explaining is an effective activity to enhance learning.In prior studies, students were instructed to explain the contents after completing an entire learning phase.Explaining at the end of a learning phase, however, may be less apt to support comprehension monitoring and subsequent regulation activities.In two experiments, we investigated whether explaining in earlier phases of studying (i.e., in-between explaini…
Shifting online
Instructing students on effective sequences of examples and problems
Nowadays, students often practice problem‐solving skills in online learning environments with the help of examples and problems. This requires them to self‐regulate their learning. It is questionable how novices self‐regulate their learning from examples and problems and whether they need support. The present study investigated the open questions (1) to what extent students' (novices) task selections align with instructional design principles and…
How do higher education students regulate their learning with video modeling examples, worked examples, and practice problems
Presenting novices with examples and problems is an effective and efficient way to acquire new problem-solving skills. Nowadays, examples and problems are increasingly presented in computer-based learning environments, in which learners often have to self-regulate their learning (i.e., choose what type of task to work on and when). Yet, it is questionable how novices self-regulate their learning from examples and problems, and to what extent thei…
Learning by explaining through digital devices
Recent meta-analytical evidence shows that learning by explaining through digital devices (e.g., computers or tablets) is effective, but also reveals substantial heterogeneity in effect sizes. The present study was designed to shed light on two theoretically plausible moderators of such learning by digital explaining: the modality of (oral) explaining (audio + visual vs. audio only) and learners' level of the personality trait of extraversion. We…
Combining non-interactive teaching and drawing fosters conceptual knowledge but not monitoring accuracy from guided inquiry in science learning
When is observing failure productive? Investigating the role of solution diversity in vicarious failure
Prior research has shown that Productive Failure (PF), where learners attempt (and fail) to solve a problem prior to receiving instruction, is more effective for conceptual knowledge acquisition than receiving instruction first (Direct Instruction; DI). Higher diversity in generated solution attempts seemed positively associated with conceptual knowledge acquisition. The present study investigated whether observing another student’s attempts to s…
Psychology (8 works) · Mathematics education (7 works) · Computer Science (6 works) · Innovative Teaching and Learning Methods (6 works) · Visual and Cognitive Learning Processes (6 works) · Cognitive psychology (4 works) · Artificial Intelligence (3 works) · Educational psychology (3 works) · Educational Strategies and Epistemologies (3 works) · Pedagogy (3 works)