Visual Learning Research Articles

Time courses of brain plasticity underpinning visual motion perceptual learning

Visual perceptual learning (VPL) refers to a long-term improvement of visual task performance through training or experience, reflecting brain plasticity even in adults. In human subjects, VPL has been mostly studied using functional magnetic resonance imaging (fMRI). However, due to the low temporal resolution of fMRI, how VPL affects the time course of visual information processing is largely unknown. To address this issue, we trained human subjects to perform a visual motion direction discrimination task. Their behavioral performance and magnetoencephalography (MEG) signals responding to the motion stimuli were measured before, immediately after, and two weeks after training. Training induced a long-lasting behavioral improvement for the trained direction. Based on the MEG signals from occipital sensors, we found that, for the trained motion direction, VPL increased the motion direction decoding accuracy, reduced the motion direction decoding latency, enhanced the direction-selective channel response, and narrowed the tuning profile. Following the MEG source reconstruction, we showed that VPL enhanced the cortical response in early visual cortex (EVC) and strengthened the feedforward connection from EVC to V3A. These VPL-induced neural changes co-occurred in 160–230 ms after stimulus onset. Complementary to previous fMRI findings on VPL, this study provides a comprehensive description on the neural mechanisms of visual motion perceptual learning from a temporal perspective and reveals how VPL shapes the time course of visual motion processing in the adult human brain.

Neural correlates of category learning in monkey inferior temporal cortex.

Area TE is required for normal learning of visual categories based on perceptual similarity. To evaluate whether category learning changes neural activity in area TE, we trained two monkeys (both male) implanted with multi-electrode arrays to categorize natural images of cats and dogs. Neural activity during a passive viewing task was compared pre- and post-training. After the category training, the accuracy of abstract category decoding improved. Single units became more category-selective, the proportion of single units with category-selectivity increased, and units sustained their category-specific responses for longer. Visual category learning thus appears to enhance category separability in area TE by driving changes in the stimulus selectivity of individual neurons and by recruiting more units to the active network.Significance statement Neurons in Area TE are known to respond selectively to a small number of visual stimuli. Here we demonstrate that the neural activity in area TE is modulated by category learning of natural images (cats and dogs), thus demonstrating that this region is capable of undergoing rapid plastic changes in adult primates.

<b>Insights From the Frontlines: Students' Perceptions of Teaching Methods in a Nigerian Medical School </b>

Background The teaching skills of the teachers impact the learning outcomes, and it is expected that learning can be enhanced through appropriate instructional strategies that will optimally help the students. An understanding of student’s perception of the available teaching methods will provide insight into what the challenges are, and how this information can be used to further optimize learning outcomes. Methods A qualitative phenomenology study using focus group discussions among 41 clinical medical students in a developing Nigerian medical school. An inductive thematic analysis was performed on the transcribed recorded data from the group discussions. Results Six themes emerged: participation, clarity and applicability, encouragement and feedback, teaching aids, students-teachers relationship, and learning environment. Students preferred problem-based learning and small group teaching, perceiving didactic lectures as lengthy and boring. They emphasized the need for teachers to use real-world examples, provide feedback, and adopt student-centered approaches. The majority of students preferred visual learning aids but noted inadequate infrastructure and resources for their preferences. Conclusions This study highlights the importance of student-centered teaching methods, incorporating visual aids and problem-based learning, to enhance engagement and retention. Teachers should adapt their instructional strategies to cater to diverse learning styles and promote interactive learning. The study suggests retraining clinical teachers to adopt student-centered approaches and utilize available resources effectively. By prioritizing student feedback and adopting inclusive teaching methods, medical educators can optimize learning outcomes and prepare students for the demands of healthcare practice. Keywords: medical, students, perceptions, teaching, methods.

Visual context learning based on cross-modal knowledge for continuous sign language recognition

Visual context learning based on cross-modal knowledge for continuous sign language recognition

Depth-prior-based range-gated 3D imaging method: integration of optical property into visual learning

3D Range-gated Imaging (3DRGI) has great potential for long-range detection in adverse weather conditions. Recently, vision-guided 3DRGI has brought new perspectives to this area as it overcomes hardware limitations and greatly increases flexibility. However, existing vision-guided methods do not consider the optical properties of range-gated imaging, which results in low accuracy. This paper proposes a depth-prior-based 3DRGI method to combine the advantages of optical-based and vision-guided methods. In this method, depth-prior is firstly deduced from principles of range-gated imaging and provides effective depth signals. Then, adaptive depth intervals are estimated using statistical methods, and a depth-prior-guided loss function is designed. The integration of the depth-prior-guided loss function within a vision-guided model enables focused attention on pixels with depth estimations that are inconsistent with the depth prior, thereby refining the overall accuracy of the depth map. To prove the feasibility of the proposed method, comparison experiments and ablation studies have been performed. The results show that the root mean square error improved by more than 12% under adverse weather conditions.

Analysis of Learning Styles Based on Indonesian Language Learning Outcomes in Elementary School Students

Understanding students' learning styles is a key factor in effective learning, as it helps teachers optimize the teaching and learning process and improve student success. This study aims to examine the relationship between students' learning styles and learning outcomes in the Indonesian language subject. The research uses a survey method with a sample of 46 fifth-grade elementary school students using saturated sampling techniques. The results indicate that the majority of students have a kinesthetic learning style (43.5%), followed by visual learning styles (30.4%) and auditory styles (26.1%). The learning outcomes of visual learners are higher compared to the others, with an average score of 84.3 in the good category, while auditory learners perform better than kinesthetic learners but lower than visual learners, with an average score of 81.4 in the fair category, whereas kinesthetic learners have lower results compared to the others, with an average score of 79.5 in the fair category. This suggests that a teaching process that does not consider the diversity of learning styles can negatively impact students' learning outcomes. Therefore, teachers need to pay attention to students' learning styles to enhance learning effectiveness so that students' learning outcomes can be optimal.

Infrared Image Generation Based on Visual State Space and Contrastive Learning

The preparation of infrared reference images is of great significance for improving the accuracy and precision of infrared imaging guidance. However, collecting infrared data on-site is difficult and time-consuming. Fortunately, the infrared images can be obtained from the corresponding visible-light images to enrich the infrared data. To this end, this present work proposes an image translation algorithm that converts visible-light images to infrared images. This algorithm, named V2IGAN, is founded on the visual state space attention module and multi-scale feature contrastive learning loss. Firstly, we introduce a visual state space attention module designed to sharpen the generative network’s focus on critical regions within visible-light images. This enhancement not only improves feature extraction but also bolsters the generator’s capacity to accurately model features, ultimately enhancing the quality of generated images. Furthermore, the method incorporates a multi-scale feature contrastive learning loss function, which serves to bolster the robustness of the model and refine the detail of the generated images. Experimental results show that the V2IGAN method outperforms existing typical infrared image generation techniques in both subjective visual assessments and objective metric evaluations. This suggests that the V2IGAN method is adept at enhancing the feature representation in images, refining the details of the generated infrared images, and yielding reliable, high-quality results.

Impact of Cognitive and Psychological Functions in Relapsing-Remitting Multiple Sclerosis: A Cross-Sectional Study.

To compare the cognitive functions and trait anxiety in patients diagnosed with relapsing-remitting multiple sclerosis (RRMS) to those of matched healthy controls (HCs). In addition, the study aims to investigate the correlations among cognitive functions, anxiety, depression, and quality of life (QOL) in this clinical population. The sample included RRMS patients (n = 21) and an equal number of age-, education-, and sex-matched HCs. Participants were assessed on the Indian version of the Wechsler Adult Intelligence Scale-IV, auditory and visual learning and memory, and visual-spatial construction and memory. RRMS patients were also assessed for levels of anxiety, depression, and their QOL. Comparative analyses between RRMS patients and HCs were carried out for neuropsychological assessments. Correlations among cognitive functions, anxiety, depression, and QOL in RRMS patients were examined. RRMS patients showed significant deficits across various cognitive domains, including processing speed and verbal learning, compared to HCs (P < 0.05). In addition, they reported higher levels of trait anxiety compared to HCs (P < 0.01), along with moderate state anxiety and mild depression. A significant correlation among anxiety, depression, and QOL was observed in RRMS patients. This study highlights significant cognitive impairments and psychological distress experienced by RRMS individuals, underscoring the critical need for comprehensive care addressing both cognitive impairments and psychological distress to enhance QOL.

Development of Learning Video Media in Biology Subjects

The purpose of this study is to produce valid and practical learning video media for use in the learning process. This research is a development research used to produce a product in the form of learning video media. The stages in this development include: planning stage, design stage, and development stage. The subjects in this study were 2 validators consisting of learning media experts and content or learning media material experts, 31 grade XI science students and 1 Biology subject teacher. Data collection techniques used observation, interviews, questionnaires and documentation. The data analysis techniques used were Qualitative Descriptive Analysis, and Descriptive Static Analysis. Research on this offers novelty in the form of more visual and interactive learning media, allowing students to understand complex biological concepts through interesting graphical and animated representations. In addition, these learning videos provide flexibility for students to learn independently and repeatedly, thus improving conceptual understanding and accommodating various learning styles.

THE EFFECT OF COLOUR-CODING ON LEARNING ENGLISH SENTENCE STRUCTURE

Colour carries a psychologically relevant meaning, and the colours we see affect our psychological performance. Colour-coding impacts learners’ cognitive processing as material-oriented interventions in multimedia learning. For educational purposes, colours can be used to stimulate neural activity, allowing pupils to learn, memorize, and retain new information more efficiently. Especially for those who are visual learners, the brighter the colours are, the more they are able to capture the attention for particular types of information. (Elliot and Maier: 2012). Colour-Coding Strategy can help pupils make connections, gain knowledge and have a positive impact on attention inside the classroom. So it is not a kind of fun. Using such a strategy in teaching and learning grammar can be as simple as just asking your pupils to take out their booklets and colouring pens and markers. The current research focuses on determining the effectiveness of using colour-coding as a better tool for learning sentence structure at the primary level. In light of the aim, the research’s null hypothesis has been formulated to be tested. The design of one group has been adopted, pre and post-tests used. The sample includes (32) female pupils who are randomly selected from Qubat Al Sakhrah primary school in Mosul city.

BI‐LAVA: Biocuration With Hierarchical Image Labelling Through Active Learning and Visual Analytics

AbstractIn the biomedical domain, taxonomies organize the acquisition modalities of scientific images in hierarchical structures. Such taxonomies leverage large sets of correct image labels and provide essential information about the importance of a scientific publication, which could then be used in biocuration tasks. However, the hierarchical nature of the labels, the overhead of processing images, the absence or incompleteness of labelled data and the expertise required to label this type of data impede the creation of useful datasets for biocuration. From a multi‐year collaboration with biocurators and text‐mining researchers, we derive an iterative visual analytics and active learning (AL) strategy to address these challenges. We implement this strategy in a system called BI‐LAVA—Biocuration with Hierarchical Image Labelling through Active Learning and Visual Analytics. BI‐LAVA leverages a small set of image labels, a hierarchical set of image classifiers and AL to help model builders deal with incomplete ground‐truth labels, target a hierarchical taxonomy of image modalities and classify a large pool of unlabelled images. BI‐LAVA's front end uses custom encodings to represent data distributions, taxonomies, image projections and neighbourhoods of image thumbnails, which help model builders explore an unfamiliar image dataset and taxonomy and correct and generate labels. An evaluation with machine learning practitioners shows that our mixed human–machine approach successfully supports domain experts in understanding the characteristics of classes within the taxonomy, as well as validating and improving data quality in labelled and unlabelled collections.

Humanistic data art visualization for analyzing learner growth in Challenge Based Learning programs.

This perspective article investigates the potential of applying artistic or "humanistic" data visualization to improve the understanding of learner's growth in the context of highly dynamic, learner-centric and experiential educational programs. The article explores the possibility of leveraging a more humanistic or esthetically driven approach to visual learning analytics in the context of programs using Challenge Based Learning (CBL) as a learning framework. CBL is a relatively new and rapidly expanding educational framework grounded on a rich tradition of constructivist, progressive and experiential learning theories. To illustrate the concept, the authors created two data visualizations, designed to offer a comprehensive overview of learners' growing perceptions. The artistic infographic also provides program managers' insights into class dynamics and the programs' overall impact, enhancing the understanding and effectiveness of student-centered learning journeys. Some suggestions for future research are offered.

Visual Perceptual Learning of Form-Motion Integration: Exploring the Involved Mechanisms with Transfer Effects and the Equivalent Noise Approach.

Background: Visual perceptual learning plays a crucial role in shaping our understanding of how the human brain integrates visual cues to construct coherent perceptual experiences. The visual system is continually challenged to integrate a multitude of visual cues, including form and motion, to create a unified representation of the surrounding visual scene. This process involves both the processing of local signals and their integration into a coherent global percept. Over the past several decades, researchers have explored the mechanisms underlying this integration, focusing on concepts such as internal noise and sampling efficiency, which pertain to local and global processing, respectively. Objectives and Methods: In this study, we investigated the influence of visual perceptual learning on non-directional motion processing using dynamic Glass patterns (GPs) and modified Random-Dot Kinematograms (mRDKs). We also explored the mechanisms of learning transfer to different stimuli and tasks. Specifically, we aimed to assess whether visual perceptual learning based on illusory directional motion, triggered by form and motion cues (dynamic GPs), transfers to stimuli that elicit comparable illusory motion, such as mRDKs. Additionally, we examined whether training on form and motion coherence thresholds improves internal noise filtering and sampling efficiency. Results: Our results revealed significant learning effects on the trained task, enhancing the perception of dynamic GPs. Furthermore, there was a substantial learning transfer to the non-trained stimulus (mRDKs) and partial transfer to a different task. The data also showed differences in coherence thresholds between dynamic GPs and mRDKs, with GPs showing lower coherence thresholds than mRDKs. Finally, an interaction between visual stimulus type and session for sampling efficiency revealed that the effect of training session on participants' performance varied depending on the type of visual stimulus, with dynamic GPs being influenced differently than mRDKs. Conclusion: These findings highlight the complexity of perceptual learning and suggest that the transfer of learning effects may be influenced by the specific characteristics of both the training stimuli and tasks, providing valuable insights for future research in visual processing.

Framework of Computer Science Learning Through Hybrid Service Learning Oriented Visual Toward the Continuum of Visualization Thinking and Generic Skills

Computer Science learning requires students to think logically and understand its practical implementation in real-life situation clearly. However, the lack of learning activities that bridge the gap between theory and practice hinders their ability to depict learned concepts in real-world scenarios and master generic skills. Therefore, Computer Science education necessitates visualising learning concepts in real-life contexts, such as implementing Service Learning activities. However, in the current post-COVID-19 endemic situation, it is not feasible to implement this approach fully face-to-face. Thus, integrating Service Learning activities through technology-mediated means is essential in Computer Science education. Hybrid Service Learning activities, using technology as a medium, are instructional designs that provide opportunities for students to apply theoretical knowledge practically in real-life situations. Therefore, in this study, Computer Science learning activities were designed with visual materials through a hybrid service learning website to support the continuum of students' visual thinking and their generic skills. Subsequently, the effects of Computer Science learning activities on the continuum of students' visual thinking, level of generic skills, and perception were analyzed. A quasi-experimental study design was used, which involved a total of 27 respondents and took 15 weeks to complete. The research data was analyzed using descriptive analysis and inferential statistics. The results of paired t-test for the continuum of students' visual thinking levels, including visual thinking, visual learning, and visual communication, indicated an improvement with a significant difference of [p&lt;0.05] between the pre- and post-activities. In terms of students' generic skills levels, the paired t-test for the pre-Service Learning [PS], during-Service Learning [DS], and post-Service Learning [AS] phases showed a significant difference of [p&lt;0.05], which indicated an increase in students' mastery of skills and changes between each phase. Furthermore, students' perceptions revealed positive feedback towards hybrid service learning. Overall, based on the findings of this study, a framework for visual-based hybrid service learning was developed as a guide for Computer Science education to support the continuum of students' visual thinking and their level of generic skills.

Relationship between duration of undiagnosed illness, clinical features and cognitive impairment in bipolar disorder

Purpose: It is believed that a delay in the diagnosis of bipolar disorder may adversely affect the clinical course and outcome. This study aimed to investigate the relationship between diagnostic delay and clinical variables, as well as neurocognitive and social cognitive disorders Materials and methods: Eighty-four patients with bipolar disorder in remission were included in the study. Participants were evaluated using a neuropsychological battery that assessed verbal memory and learning, visual memory and learning, verbal fluency, attention, processing speed, executive functions, working memory, and social cognition. Results: The duration of undiagnosed illness was longer in patients with bipolar II disorder, those without psychotic features, those with at least one suicide attempt, those whose first episode was depressive, and those currently on antidepressants. A significant positive correlation was found between the duration of undiagnosed illness and scores on the Controlled Oral Word Association Test, total number of episodes, hypomanic episodes, depressive episodes, and their respective durations. Conversely, a significant negative correlation was found between the duration of undiagnosed illness and both the number and duration of manic episodes. Conclusion: We found that a delay in diagnosis and treatment was associated with more recurrences in bipolar disorder, an increased number of depressive episodes, and at least one lifetime suicide attempt. However, the association between extended periods of untreated illness and poor clinical and functional outcomes did not align with cognitive impairment.

E-Learning Design for Older Adults in the United States

As global populations age, there is an urgent need to address the unique learning requirements of older adults in the context of e-learning. This study builds upon prior work to investigate the connections between older adults’ cognitive profiles, learning preferences, and attitudes toward technology in the United States. Through a survey of 203 U.S. adults aged 55 and above, data were collected on participant demographics, learning preferences, and attitudes towards technology. The results reveal a tech-savvy sample that is most comfortable with everyday applications and favors practical, visual learning approaches. Key findings include high levels of internet and smartphone adoption, varying confidence levels across different mobile applications, and strong preferences for step-by-step instructions, examples, and graphics in e-learning modules. This mixed-method study serves as a foundation for future research aimed at increasing the adoption and effectiveness of e-learning among older adults in the U.S. and globally, ultimately contributing to the overall quality of life and support for active-aging initiatives.

The Development of Geo-Math Application by Integrating Geo-Gebra Applets to Improve Students’ Spatial Ability

Geometry can be challenging for students due to its abstract nature; The difficulty is often associated with low spatial abilities; to overcome these challenges, educators can employ dynamic and visual learning approaches to help students learn and understand geometric concepts more effectively. This study aimed to develop a Geo Math application by integrating the GeoGebra applets on geometry that fulfill valid, practical, and effective aspects that are expected to improve spatial abilities. This research utilized development research using the ADDIE model, which consists of 5 stages: analysis, design, development, and trial implementation. It went through several trial stages consisting of validation experts, one-to-one trials, and small group trials, and the evaluation stage was carried out through a pre-post-test quasi-experimental study. Based on the results, it can be concluded that the Geo Math application was very feasible to support the implementation of learning mathematics, especially in learning geometric transformations, which could assist students in constructing concepts from various transformations effectively. The interactive and dynamic nature of GeoGebra applets within the application allowed students to visualize and manipulate geometric objects and could make abstract mathematical concepts more concrete and accessible, which could improve students’ spatial abilities.

PENGGUNAAN E-MODUL BERBASIS KEARIFAN LOKAL PANTURA DALAM MENINGKATKAN KECERDASAN LOGIS PADA SISWA AUTIS

This study analyzes the effectiveness of interactive e-modules based on Pantura local wisdom in teaching animal and plant body parts to autistic students in a fourth-grade class at SDLB Sunan Kudus. Employing a qualitative descriptive approach, the research utilized structured interviews with the class teacher and direct observations of classroom activities to gather data on the implementation of the e-modules and their impact on student engagement and learning outcomes. Findings reveal that these locally grounded e-modules significantly enhance the logical intelligence and problem-solving skills of autistic students by facilitating a more engaging learning experience that connects educational content with their local environment, thereby increasing motivation and participation in science education. The study highlights the necessity of using concrete and visual learning materials, as autistic students benefit from tangible resources that aid comprehension. Additionally, the integration of technology, such as voice recorders and interactive media, supports the learning process by making it more accessible and enjoyable. The results emphasize the critical role of culturally relevant teaching methods and the need for ongoing guidance and supervision to foster the academic and cognitive growth of students with special needs, contributing to the understanding of effective pedagogical strategies in special education and advocating for the incorporation of local wisdom and technological tools to enhance learning outcomes for autistic students.

ASSESSING THE INFLUENCE OF CONTINUOUS PROFESSIONAL DEVELOPMENT PROGRAMMES ON THE TEACHING METHODOLOGIES OF HISTORY TEACHERS IN SENIOR SECONDARY SCHOOLS IN RIVERS STATE, NIGERIA

The study assessed the influence of continuous professional development programmes on the teaching methodologies of history teachers in senior secondary schools in Rivers State. Three research questions with corresponding three hypotheses guided the study. The study adopted descriptive survey designs. The population for the study consisted of 604 History teachers in public senior secondary schools in Rivers State. A retrieved sample was used for analysis, and there were 280 respondents. Stratified random sampling was used to stratify Rivers State into Rivers East, Rivers West and Rivers South East senatorial districts. Stage Quota sampling technique was applied to select History teachers from each senatorial district in Rivers State. The instrument constructed was a questionnaire titled “Influence of Continuous Professional Development Programmes on the Teaching Methodologies of History Teachers Questionnaire (ICPDPTMHTQ). The content and face validity instrument was validated by experts and History head teachers. Cronbach alpha was used to determine the reliability index of 0.80. Out of 302 copies of the instrument distributed to the respondents, 280 copies of the instruments were returned. Multiple Regression statistics method associated with ANOVA and t-test was used to answer research questions and test the hypotheses at 0.05 level of significance. The findings revealed that Continuous professional development significantly enhances teaching methods for history teachers in Rivers State. However, project-based learning, field trips, virtual tours, game-based learning, visual learning, and the Socratic method show no significant influence, indicated by high p-values and low coefficients. The study recommended that school administrators should be encouraged to offer CPD programmes that include training on innovative teaching strategies, like project-based learning and field trips, to enhance the overall effectiveness of history instruction.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0702/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Learning incremental audio–visual representation for continual multimodal understanding

Deep learning methods have demonstrated remarkable success in processing static datasets for various video tasks. However, when confronted with continuous data streams, these approaches often encounter the challenge of catastrophic forgetting. This phenomenon leads to a significant decline in overall performance when learning new classes incrementally. Moreover, existing methods tend to overlook the correlation between audio and visual modalities in video incremental learning, despite their joint significance in scene comprehension. How to continuously learn from new classes while maintaining the knowledge of old videos with limited storage and computing resources is becoming imperative in the field of multimodal learning. In this paper, we introduce CavRL, a pioneering benchmark for audio–visual representation learning under class incremental scenarios. To mitigate catastrophic forgetting, we propose a rehearsal-based training approach that leverages a small exemplar set from previous classes. Our approach constrains the memory buffer within strict storage limits, optimizing exemplar selection by learning correlative audio–visual representations. Additionally, we employ a distillation method to mitigate forgetting in a self-supervised manner. Evaluations on two prevalent multimodal tasks: audio–visual event classification and audio–visual speaker recognition, which demonstrate that CavRL outperforms existing state-of-the-art incremental learning methods across various settings. We anticipate that CavRL will significantly advance research in continual multimodal learning.