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11. Mixed-Methods Exploration of Students' Motivation in Using Augmented Reality in Neuroanatomy Education with Prosected Specimens

Author

Bölek, Kerem A., De Jong, Guido, Van der Zee, Catharina E. E. M., Cappellen van Walsum, Anne-Marie, and Henssen, Dylan J. H. A.

Abstract

The use of augmented reality (AR) in teaching and studying neuroanatomy has been well researched. Previous research showed that AR-based learning of neuroanatomy has both alleviated cognitive load and was attractive to young learners. However, how the attractiveness of AR effects student motivation has not been discovered. Therefore, the motivational effects of AR were investigated in this research by the use of quantitative and qualitative methods. Motivation elicited by the GreyMapp-AR, an AR application, was investigated in medical and biomedical sciences students (n = 222; mean age: 19.7 ± 1.4 years) using the instructional measure of motivation survey (IMMS). Additional components (i.e., attention, relevance, confidence, and satisfaction) were also evaluated with motivation as measured by IMMS. Additionally, 19 students underwent audio-recorded individual interviews which were transcribed for qualitative analysis. Males regarded the relevance of AR significantly higher than females (P < 0.024). Appreciation of the GreyMapp-AR program was found to be significantly higher in students studying biomedical sciences as compared to students studying medicine (P < 0.011). Other components and scores did not show significant differences between student groups. Students expressed that AR was beneficial in increasing their motivation to study subcortical structures, and that AR could be helpful and motivating for preparing an anatomy examination. This study suggests that students are motivated to study neuroanatomy by the use of AR, although the components that make up their individual motivation can differ significantly between groups of students.

Published
2022
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12. E-Learning Three-Dimensional Anatomy of the Brainstem: Impact of Different Microscopy Techniques and Spatial Ability

Author

Cappellen van Walsum, Anne-Marie van and Henssen, Dylan J. H. A.

Abstract

Polarized light imaging (PLI) is a new method which quantifies and visualizes nerve fiber direction. In this study, the educational value of PLI sections of the human brainstem were compared to histological sections stained with Luxol fast blue (LFB) using e-learning modules. Mental Rotations Test (MRT) was used to assess the spatial ability. Pre-intervention, post-intervention, and long-term (1 week) anatomical tests were provided to assess the baseline knowledge and retention. One-on-one electronic interviews after the last test were carried out to understand the students' perceptions of the intervention. Thirty-eight medical students, (19 female and 19 males, mean age 21.5 ± SD 2.4; median age: 21.0 years) participated with a mean MRT score of 13.2 ± 5.2 points and a mean pre-intervention knowledge test score of 49.9 ± 11.8%. A significant improvement in both, post-intervention and long-term test scores occurred after learning with either PLI or LFB e-learning module on brainstem anatomy (both P < 0.001). No difference was observed between groups in post-intervention test scores and long-term test scores (P = 0.913 and P = 0.403, respectively). A higher MRT-score was significantly correlated with a higher post-intervention test score (r[subscript k] = 0.321; P < 0.05, respectively), but there was not a significant association between the MRT- and the long-term scores (r[subscript k] = -0.078; P = 0.509). Interviews (n = 10) revealed three major topics: Learning (brainstem) anatomy by use of e-learning modules; The "need" of technological background information when studying brainstem sections; and Mnemonics when studying brainstem anatomy. Future studies should assess the cognitive burden of cross-sectional learning methods with PLI and/or LFB sections and their effects on knowledge retention.

Published
2022
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27. Neuroanatomy Learning: Augmented Reality vs. Cross-Sections

Author

Henssen, Dylan J. H. A., van den Heuvel, Loes, De Jong, Guido, Vorstenbosch, Marc A. T. M., van Cappellen van Walsum, Anne-Marie, Van den Hurk, Marianne M., Kooloos, Jan G. M., and Bartels, Ronald H. M. A.

Abstract

Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or using cross-sections of the brain. Prior to two practical assignments, a pretest (extended matching questions, double-choice questions and a test on cross-sectional anatomy) and a mental rotation test (MRT) were completed. Sex and MRT scores were used to stratify students over the two groups. The two practical assignments were designed to study (1) general brain anatomy and (2) subcortical structures. Subsequently, participants completed a posttest similar to the pretest and a motivational questionnaire. Finally, a focus group interview was conducted to appraise participants' perceptions. Medical and biomedical students (n = 31); 19 males (61.3%) and 12 females (38.7%), mean age 19.2 [plus or minus] 1.7 years participated in this experiment. Students who worked with cross-sections (n = 16) showed significantly more improvement on test scores than students who worked with GreyMapp-AR (P = 0.035) (n = 15). Further analysis showed that this difference was primarily caused by significant improvement on the cross-sectional questions. Students in the cross-section group, moreover, experienced a significantly higher germane (P = 0.009) and extraneous cognitive load (P = 0.016) than students in the GreyMapp-AR group. No significant differences were found in motivational scores. To conclude, this study suggests that AR applications can play a role in future anatomy education as an add-on educational tool, especially in learning three-dimensional relations of anatomical structures.

Published
2020
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33. Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study

Author

van den Elshout, Rik, primary, Herings, Siem D. A., additional, Mannil, Manoj, additional, Gijtenbeek, Anja M. M., additional, ter Laan, Mark, additional, Smeenk, Robert J., additional, Meijer, Frederick J. A., additional, Scheenen, Tom W. J., additional, and Henssen, Dylan J. H. A., additional

Published
2023
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38. PET Imaging and Protein Expression of Prostate-Specific Membrane Antigen in Glioblastoma: A Multicenter Inventory Study

Author

van Lith, Sanne A.M., primary, Pruis, Ilanah J., additional, Tolboom, Nelleke, additional, Snijders, Tom J., additional, Henssen, Dylan, additional, ter Laan, Mark, additional, te Dorsthorst, Maarten, additional, Leenders, William P.J., additional, Gotthardt, Martin, additional, Nagarajah, James, additional, Robe, Pierre A., additional, De Witt Hamer, Philip, additional, Hendrikse, Harry, additional, Oprea-Lager, Daniela E., additional, Yaqub, Maqsood, additional, Boellaard, Ronald, additional, Wesseling, Pieter, additional, Balvers, Rutger K., additional, Verburg, Frederik A., additional, Harteveld, Anita A., additional, Smits, Marion, additional, van den Bent, Martin, additional, van Zanten, Sophie E.M. Veldhuijzen, additional, and van de Giessen, Elsmarieke, additional

Published
2023
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39. Augmented reality—The way forward in patient education for intracranial aneurysms? A qualitative exploration of views, expectations and preferences of patients suffering from an unruptured intracranial aneurysm regarding augmented reality in patient education

Author

Urlings, Julie, primary, Abma, Inger, additional, Aquarius, René, additional, Aalbers, Marlien, additional, Bartels, Ronald, additional, Maal, Thomas, additional, Henssen, Dylan, additional, and Boogaarts, Jeroen, additional

Published
2023
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42. Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma

Author

Henssen, Dylan, primary, Leijten, Lars, additional, Meijer, Frederick J. A., additional, van der Kolk, Anja, additional, Arens, Anne I. J., additional, ter Laan, Mark, additional, Smeenk, Robert J., additional, Gijtenbeek, Anja, additional, van de Giessen, Elsmarieke M., additional, Tolboom, Nelleke, additional, Oprea-Lager, Daniela E., additional, Smits, Marion, additional, and Nagarajah, James, additional

Published
2023
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49. Predicting Meningioma Resection Status: Use of Deep Learning

Author

Akkurt, Burak Han, primary, Wanderer, Stefan, additional, Schwyzer, Lucia, additional, Berberat, Jatta, additional, Henssen, Dylan J.H.A., additional, Sartoretti, Thomas, additional, Sartoretti, Elisabeth, additional, Musigmann, Manfred, additional, Brokinkel, Benjamin, additional, Stummer, Walter, additional, Heindel, Walter, additional, Remonda, Luca, additional, and Mannil, Manoj, additional

Published
2022
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