Experiential Learning, Spatial Visualization and Metacognition: An Exercise with the “Blank Page” Technique for Learning Anatomy by Helen L. Naug, Natalie J. Colson, Daniel Donner

“…Discussion: The blank page activity has merit in student engagement and facilitation of the learning of anatomy by broadening the scope of instruction to encompass multimodal learning preferences, metacognition and visual spatial thinking.…”
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Realistic Image Generation from Text by Using BERT-Based Embedding by Sanghyuck Na, Mirae Do, Kyeonah Yu, Juntae Kim

“…Recently, in the field of artificial intelligence, multimodal learning has received a lot of attention due to expectations for the enhancement of AI performance and potential applications. …”
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An Empirical Study on Multimodal Activity Clustering of Android Applications by Sungmin Choi, Hyeon-Tae Seo, Yo-Sub Han

“…Finally, by fusing the two models, we propose an activity clustering approach using multimodal learning. Since there are no labels in the dataset, we make 2000 labeled data for evaluation. …”
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A Cross-Modal Dynamic Attention Neural Architecture to Detect Anomalies in Data Streams from Smart Communication Environments by Konstantinos Demertzis, Konstantinos Rantos, Lykourgos Magafas, Lazaros Iliadis

“…Specifically, the proposed model uses multimodal learning tasks where the input data comes from different cyber modalities. …”
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A survey on learning styles of undergraduate medical students and its associated factors by Diwakar Dhurandhar, Tripti Chandrakar, Deepti Chandrakar, Jagriti Agrawal

“…Seventy one percent of the subjects were found to have multimodal learning preferences whereas 29% were unimodal learners. …”
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Multimodal Representation Learning for Medical Image Analysis by Liao, Ruizhi

“…The experiments described in this thesis demonstrate the advances of the multimodal learning approaches in the application of chest x-ray analysis.…”
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Supporting Students’ Science Content Knowledge and Motivation through Project-Based Inquiry (PBI) Global in a Cross-School Collaboration by Hiller A. Spires, Marie P. Himes, Erin Krupa

“…The data sources included pre-/post-tests on science content and student motivation (n = 75), transcripts from student focus groups (n = 26), and students’ multimodal learning products (n = 18 teams). The quantitative findings indicated School B students were more motivated by the project than School A students, which mirrored student performance. …”
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Intelligent Recognition Using Ultralight Multifunctional Nano-Layered Carbon Aerogel Sensors with Human-Like Tactile Perception by Huiqi Zhao, Yizheng Zhang, Lei Han, Weiqi Qian, Jiabin Wang, Heting Wu, Jingchen Li, Yuan Dai, Zhengyou Zhang, Chris R. Bowen, Ya Yang

“…The tactile system with multimodal learning algorithms has universality and can accommodate object recognition tasks in various application scenarios (e.g., Mars and Kitchen).…”
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CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions by Shashi Kant Shankar, Adolfo Ruiz-Calleja, Luis P. Prieto, María Jesús Rodríguez-Triana, Pankaj Chejara, Sandesh Tripathi

“…Multimodal Learning Analytics (MMLA) solutions aim to provide a more holistic picture of a learning situation by processing multimodal educational data. …”
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SMoCo: A Powerful and Efficient Method Based on Self-Supervised Learning for Fault Diagnosis of Aero-Engine Bearing under Limited Data by Zitong Yan, Hongmei Liu

“…Using the data augmentation method, SMoCo performs feature extraction on vibration signals from both time and frequency domains, which is called signal multimodal learning (SML). It has been proved by experiments that after pre-training with artificially injected fault bearing data, SMoCo can learn a powerful and robust feature extractor, which can greatly improve the accuracy no matter the target diagnostic data with different working conditions, different failure modes, or even different types of equipment from the pre-training dataset. …”
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Use of wearable devices in the teaching-learning process: a systematic review of the literature by Leonardo David Glasserman-Morales, Leonardo David Glasserman-Morales, Martina Carlos-Arroyo, Jessica Alejandra Ruiz-Ramirez, Carolina Alcantar-Nieblas

“…Multimodal learning analytics (MMLA) has emerged as an encompassing approach to data collection, facilitating the analysis of student interactions across a variety of resources. …”
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Large-scale acoustic scene analysis with deep residual networks by Ford, Logan H.

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Editorial by Christian Gütl

“…Prieto, María Jesús Rodríguez-Triana, Pankaj Chejara, and Sandesh Tripathi discuss a modular and modifiable infrastructure for data preparation, organization, and fusion to partially support the development of context-aware multimodal learning analytics solutions. Enjoy Reading!…”
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MDF-Net for abnormality detection by fusing X-rays with clinical data by Chihcheng Hsieh, Isabel Blanco Nobre, Sandra Costa Sousa, Chun Ouyang, Margot Brereton, Jacinto C. Nascimento, Joaquim Jorge, Catarina Moreira

“…Since these data modalities are in different dimensional spaces, we propose a spatial arrangement strategy, spatialization, to facilitate the multimodal learning process in a Mask R-CNN model. We performed an extensive experimental evaluation using MIMIC-Eye, a dataset comprising different modalities: MIMIC-CXR (chest X-ray images), MIMIC IV-ED (patients’ clinical data), and REFLACX (annotations of disease locations in chest X-rays). …”
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System design for using multimodal trace data in modeling self-regulated learning by Elizabeth Brooke Cloude, Roger Azevedo, Philip H. Winne, Gautam Biswas, Eunice E. Jang

“…In this paper, we discuss recommendations for building a multimodal learning analytics architecture for advancing research on how researchers or instructors can standardize, process, analyze, recognize and conceptualize (SPARC) multimodal data in the service of understanding learners' real-time SRL and productively intervening learning activities with significant implications for artificial intelligence capabilities. …”
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Improving RGB-Infrared Object Detection by Reducing Cross-Modality Redundancy by Qingwang Wang, Yongke Chi, Tao Shen, Jian Song, Zifeng Zhang, Yan Zhu

“…Existing RGB-infrared detection methods do not explicitly encourage RGB and infrared images to achieve effective multimodal learning. We find that when fusing RGB and infrared images, cross-modal redundant information weakens the degree of complementary information fusion. …”
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Cross-platform privacy-preserving CT image COVID-19 diagnosis based on source-free domain adaptation by Feng, Yuanyi, Luo, Yuemei, Yang, Jianfei

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Monitoring amyloidogenesis with a 3D deep-learning-guided biolaser imaging array by Chan, Kok Ken, Shang, Linwei, Qiao, Zhen, Liao, Yikai, Kim, Munho, Chen, Yu-Cheng

“…The training set, validation set, and test set of the multimodal learning model achieved outstanding classification accuracies of over 95%. …”
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Learning styles of music students and preference to study with or without music / Hawa Nor Adilah Md Yusofe by Md Yusofe, Hawa Nor Adilah

“…Results of the study found that, 55% had single learning style and 45% had multimodal learning style. Among multimodal learners, bi-modal learners comprised of 67%, tri-modal learners were 24%, and quad-modal learners were 9%. …”
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Learning style preferences: A study of Pre-clinical Medical Students in Barbados by NKEMCHO OJEH, NATASHA SOBERS-GRANNUM, UMA GAUR, ALAYA UDUPA, MD. ANWARUL AZIM MAJUMDER

“…Overall, 60.7% of high achievers used multimodal learning compared to 56.9% low achievers. Conclusion: The findings from this study indicated that the VARK tool was useful in gathering information about different learning styles, and might assist educators in designing blended teaching strategies to cater to the students’ needs as well as help the students in becoming aware of their learning style preferences to enhance learning.…”
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