Visual Learning Research Articles

Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study

This study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism of cognitive deficits in treatment-resistance. In this case‒control 3-year-follow-up longitudinal study, n = 697 patients with first-episode psychosis, aged 18 to 35, were screened for Treatment Response and Resistance in Psychosis criteria through an algorithm that assigns patients to responder, limited-response or treatment-resistant category (respectively resistant to 0, 1 or 2 antipsychotics). Assessments at baseline: MATRICS Consensus Cognitive Battery; N-methyl-D-aspartate-receptor co-agonists biomarkers in brain by MRS (prefrontal glutamate levels) and plasma (D-serine and glutamate pathways key markers). Patients were compared to age- and sex-matched healthy controls (n = 114). Results: patient mean age 23, 27% female. Treatment-resistant (n = 51) showed lower scores than responders (n = 183) in processing speed, attention/vigilance, working memory, verbal learning and visual learning. Limited responders (n = 59) displayed an intermediary phenotype. Treatment-resistant and limited responders were merged in one group for the subsequent D-serine and glutamate pathway analyses. This group showed D-serine pathway dysregulation, with lower levels of the enzymes serine racemase and serine-hydroxymethyltransferase 1, and higher levels of the glutamate-cysteine transporter 3 than in responders. Better cognition was associated with higher D-serine and lower glutamate-cysteine transporter 3 levels only in responders; this association was disrupted in the treatment resistant group. Treatment resistant patients and limited responders displayed early cognitive and persistent functioning impairment. The dysregulation of NMDAR co-agonist pathways provides underlying molecular mechanisms for cognitive deficits in treatment-resistant first-episode psychosis. If replicated, our findings would open ways to mechanistic biomarkers guiding response-based patient stratification and targeting cognitive improvement in clinical trials.

Pengaruh Pendekatan Pembelajaran TaRL (Teaching at Right Level) dalam Meningkatkan Hasil Belajar Peserta Didik Pada Pelajaran Matematika Di SMKN 8 Surabaya

The research was motivated by the problems of interest, motivation and learning outcomes of students regarding mathematics lessons in class There are those who have low, medium and high ability to understand the material and different learning styles, including visual, auditory and kinesthetic learning styles. The learning needs of these students have also not been met. So that from these problems abilities and learning styles can influence student learning outcomes. The reason behind the researchers conducting this research was the low interest in learning of students in mathematics subjects. Among the 27 students, there were only 14 (52%) students who liked mathematics and 13 (48%) students who did not like mathematics. This research aims to determine the improvement in student learning outcomes through the TARL (Teaching at Right Level) learning approach. This research uses the classroom action research (PTK) method with a quantitative approach and data collection techniques using the results of the students' pretest and posttest. The material used in this research is opportunity material in Mathematics Lessons.

Noncortical coding of biological motion in newborn chicks' brain.

Biological motion, the typical movement of vertebrates, is perceptually salient for many animal species. Newly hatched domestic chicks and human newborns show a spontaneous preference for simple biological motion stimuli (point-light displays) at birth prior to any visual learning. Despite evidence of such preference at birth, neural studies performed so far have focused on a specialized neural network involving primarily cortical areas. Here, we presented newly hatched visually naïve domestic chicks to either biological or rigid motion stimuli and measured for the first time their brain activation. Immediate Early Gene (c-Fos) expression revealed selective activation in the preoptic area of the hypothalamus and the nucleus taeniae of the amygdala. These results suggest that subpallial/subcortical regions play a crucial role in biological motion perception at hatching, paving the way for future studies on adult animals, including humans.

Al-Kahfi Puzzle Applies The Vark Learning Style In The Memorization Aspect Among Institut Kemahiran Mara Students

Al-Kahfi Puzzle is an innovative teaching aid that applies Visual (V), Auditory (A), Reading-Writing (R) and Kinesthetic (K) learning styles where it can stimulate and celebrate a variety of diverse learning approaches among students. This innovation focuses on aspect of memorizing the al-Quran, especially in memorizing the first ten verses from surah al-Kahfi. The practice of memorizing this surah is highly recommended in Islam as a way to increase one's faith and piety as well as to seek protection from end-of-life slander. However, students often face difficulties in remembering and experience difficulties in the memorization process. This is related to the correct memorization technique that suits their learning style. Therefore, al-Kahfi Puzzle aims to assist students in enhancing their memorization abilities using an engaging puzzle game that incorporates elements of the VARK approach. The objectives of this study are to identify the dominant student learning style in helping the memorization process using al-Kahfi Puzzle and to examine the effectiveness of using al-Kahfi puzzle in learning sessions for students of Islamic Studies Course at Institut Kemahiran Mara Sungai Petani. This study is qualitative in nature by using questionnaire and focused group discussion (FGD) methods. Based on the findings, al-Kahfi Puzzle meets students' VARK learning style preferences and proves beneficial in enhancing their memorization skills.

Diurnal cognitive functioning in patients with myasthenia gravis with the role of chronotype and depression: a pilot study.

Myasthenia gravis (MG) is an autoimmune disease manifested by fatigue and weakness of the skeletal muscles. Recent research has indicated that MG patients perform significantly worse than healthy controls in cognitive domains such as attention, verbal fluency, visual learning, and memory. This study aimed to investigate the diurnal fluctuations in cognitive performance in patients with myasthenia gravis in relation to selected clinical and socioeconomic parameters of the disease course, along with the role of chronotype and depression. The participants were recruited from a neurology outpatient clinic. Patients' cognitive functions were assessed twice: in the morning and the evening of the same day. Neuropsychological diagnosis included attention, memory, executive, verbal, and visuospatial abilities. Mood was measured with the Beck Depression Inventory-II and Positive and Negative Affect Schedule. The Morningness-Eveningness Questionnaire was used to examine chronotype. The analyses performed showed no significant differences between subjects and within subjects, apart from semantic fluency. Patients receiving antidepressant treatment obtained better results on attention and working memory tasks. The data obtained show that diurnal neuropsychological performance in MG patients is associated with depression. Routine assessment and treatment of mood disorders could significantly improve cognitive functioning in myasthenia gravis patients.

Efficacy of perceptual learning in low vision: A systematic review and meta-analysis.

Visual perceptual learning (PL) shows promise for enhancing visual functions in individuals with visual impairment. This systematic review aimed to evaluate the effectiveness of PL in improving visual function. Eligible studies were those examining the efficacy of PL in individuals with low vision. The review protocol was registered with the international Prospective Register of Systematic Reviews (ID CRD42022327545) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Screened studies were synthesized using random-effects meta-analysis and narrative synthesis following Synthesis Without Meta-analysis guidelines. The quality of the evidence was assessed using the Cochrane risk-of-bias tool and the JBI Critical Appraisal Tool for Quasi-Experimental studies. Fifty studies were included, covering various visual impairments and employing different PL interventions. Most studies had low risk of bias. Meta-analysis showed significant improvement in visual search for individuals with cortical blindness (Hedges' g = 0.71; 95% confidence interval, 0.48 to 0.93; p=0.002); all other analyses did not show significant improvements-reading in central vision loss and cortical blindness, and visual field in peripheral vision loss and cortical blindness. However, the narrative synthesis provided evidence showing effectiveness, particularly in individuals with central vision loss and cortical blindness, demonstrating positive effects on reading, contrast sensitivity, visual field, and motion perception. Variations in study design, PL protocols, outcome measures, and measurement methods introduced heterogeneity, limiting the analysis. The efficacy of PL in vision rehabilitation remains uncertain. Although meta-analysis results were mostly inconclusive, the narrative synthesis indicated improved visual functions following PL, consistent with individual study findings. Future research should optimize intervention parameters, explore long-term effects, and assess generalizability across diverse populations and visual impairment etiologies. Larger randomized controlled trials using standardized outcome measures are needed to advance the field.

A randomised, double-blind, placebo-controlled trial to assess dose-dependent effects of blueberries on blood pressure, glucose and cognition

Obesity can increase the risk of diseases such as type 2 diabetes mellitus and cardiovascular disease(1). Glucose control is critical to both preventing and managing diabetes and can be achieved by enhancing secretion of insulin, limiting absorption of glucose from the gut and by upregulating the use of glucose in the muscles(2). Abnormalities in glucose management(3) and blood pressure control(4) are known to impair cognitive function. Epidemiological studies report an inverse risk of type 2 diabetes with increased intake of polyphenols. These data are also supported by in vitro and animal studies reporting positive effects of polyphenols on insulin sensitivity, carbohydrate digestion and glucose regulation(5). Here we aimed to evaluate postprandial glucose metabolism, blood pressure and cognitive function following a high carbohydrate meal accompanied by different doses of anthocyanin containing blueberry drinks.A double-blind, placebo-controlled, dose-response study was designed and received ethical approval and 22 participants were recruited. Each participant attended four study days in a crossover design, separated by a minimum of 5 days during which, they consumed a high carbohydrate meal consisting of two slices of toast and one of three doses of blueberry beverage or a control beverage. Memory performance was assessed using the visual verbal learning test (VVLT), measured at baseline and 90 minutes post consumption. Glucose was monitored every 15 minutes using a continuous glucose monitor which was worn across 10 days, and blood pressure was assessed every 30 minutes for a period of 4 hours in the laboratory. Glucose area under the curve (AUC) were analysed using linear mixed models. Blood pressure and VVLT data were analysed using repeated measures ANOVA.The analysis was performed blind to condition. In total, 22 participants completed all four study visits (mean age 28 ± 5.9, mean weight 61kg ± 10.4, mean height, 1.64m ± 0.9, mean BMI 22.7 ± 2.27, N=20 female, N=2 male). There was a significant effect of treatment on total words recalled in the VVLT with best performance following condition B compared to condition C, and condition D compared to condition C (p < 0.05). Condition B also resulted in significant systolic blood pressure lowering compared to condition C (-2.47mmHg, P <0.003). There was no effect of treatment on area under the curve for glucose over 3 hours postprandial (p > 0.05).Taken together these results suggest that condition B conferred greatest benefit for memory performance and that this was associated with anthocyanin related effects on systolic blood pressure.This study was funded by the Wild Blueberry Association of North America (WBANA).

Data-Driven Diagnosis of PMSM Drive With Self-Sensing Signal Visualization and Deep Transfer Learning

Data-Driven Diagnosis of PMSM Drive With Self-Sensing Signal Visualization and Deep Transfer Learning

Towards automated, efficient, and interpretable diagnosis coffee leaf disease: A dual-path visual transformer network

Coffee leaf diseases are a collection of fungi and bacteria that attack coffee leaves, wreaking havoc on yields and putting producers in a tough financial bind. Traditional methods for leaf disease diagnosis often rely on manual observation, which is subjective, laborious, and prone to human error. Moreover, the dependence on chemical treatments to regulate diseases raises troubles about environmental sustainability and the long-term viability of coffee farming. In this study, a novel Dual-Path Visual Transformer is presented to perform real-time diagnosis of coffee leaves via collaboration between lesion segmentation path and classification path (disease and severity). A new visual transformer block, named COFFORMER, is introduced to replace the attention mechanism with an embarrassingly simple multiscale convolutional pooling operator to perform essential token mixing. The COFFORMER blocks are used to build the segmentation path in the form of U-shaped architecture and used to build the feature extraction modules in the classification path. A coffee lesion attention (CAL) is introduced to empower the classification subnetwork to focus on lesion areas received from intermediary segmentation maps. The experimental findings on public coffee leaf datasets demonstrated that the integration of visual learning in coffee farming not only boosts disease detection performance but also improves productivity, economic viability, and long-term sustainability. Our findings contribute to the agricultural community by granting a transformative solution that can be expanded to other crops, fostering global food security and sustainable farming practices.

Trochlea Dysplasia as the Major Anatomic Risk Factors for Patellofemoral Joint Instability: An Infographic as a Visual Learning Tool.

Patellofemoral instability (PFI) is a common condition in children and adolescents, ranging from mild discomfort and mal-tracking to lateral patellar dislocation [1]. A number of anatomical risk factors have been described in the literature, such as trochlear dysplasia, patella alta, excessive tibial tuberosity to trochlear groove (TT-TG) distance, patellar tilt and soft tissue alterations [2]. Among them, TD has been identified as the main anatomical risk factor with the strongest association with PFI [1, 2]. In the study by Dejour et al. [2] radiographically observed TD was identified in 96% of patients with a history of patellofemoral dislocation [1, 2]. Patients with Dejour Type D dysplasia are characterized by a prominent and convex lateral facet with a vertical connection to a hypoplastic medial facet (Figure 1), which provides inadequate tracking of the patella in the trochlea during flexion leading to patella subluxation [2]. Non-operative treatment of lateral patellar dislocation presents a rate of re-dislocation up to 70% within 24 months of the first episode [3]. Sulcus deepening trochleoplasty is indicated for Type B and D dysplasia, in order to improve patella tracking, reduce the rate of re-dislocation and achieve good functional outcomes [2, 4]. Trochlea dysplasia is defined as a shallow or flattened groove with decreased resistance to lateral patellar translation. TD can be assessed on computed tomography (CT) and magnetic resonance imaging (MRI) with the use of overlapping axial images and are able to show perfectly the global shape of the femoral trochlea [2]. The thresholds for identifying trochlear dysplasia are established based on the sulcus angle ≥ 145°, medial/lateral trochlea facet asymmetry < 40%, trochlear depth < 3 mm and lateral trochlear inclination ≤ 11° and therefore it can be used in young adolescents [4, 5]. A deep knowledge of anatomic variations and abnormalities of the patellofemoral joint, which may predispose to PFI, is crucial in order to choose the appropriate treatment for each patient.

AN ANALYSIS of MATHEMATICAL PROBLEM SOLVING PROCESS BASED on LEARNING STYLE

This research aimed to describe the process of solving mathematical problems based on the learning style of class VII students at SMP Negeri 1 Dobo. The subjects in this study consistend of three students, consisting of one students, consisting of one student with an auditory dominant learning style (SA), one student with a kinesthetic dominant learning style (SK), and one student with a visual dominant learning style (SV). Determining research subjects was carried out by distributing learning style questionnaires to 32 class VII students and then analysing them. The results of the research show that the process of solving mathematical problems is as follows: 1) SA was able to understand the given problem very well and find the correlation between recognized information and prior concept. Thus, SA could solve the problem correctly with considerably systematic solving steps; 2) SK was able to understand the given information very well and designa structured problem-solving step. However, during the implementation of the step, SK directly entered numbers without writing down the complete equation in advance; 3) SV lacked understanding the given problem and hence often asked other students how to solve the problem. Nevertheless, after several times recalling the previously learned concepts, SV started to solve the problem correctly by using a comparison and difference table. After getting the answer, SV rechecked the mathematical problem-solving process several times in order to ensure the final answer.

Rapid identification of medicinal plants via visual feature-based deep learning

BackgroundTraditional Chinese Medicinal Plants (CMPs) hold a significant and core status for the healthcare system and cultural heritage in China. It has been practiced and refined with a history of exceeding thousands of years for health-protective affection and clinical treatment in China. It plays an indispensable role in the traditional health landscape and modern medical care. It is important to accurately identify CMPs for avoiding the affected clinical safety and medication efficacy by the different processed conditions and cultivation environment confusion.ResultsIn this study, we utilize a self-developed device to obtain high-resolution data. Furthermore, we constructed a visual multi-varieties CMPs image dataset. Firstly, a random local data enhancement preprocessing method is proposed to enrich the feature representation for imbalanced data by random cropping and random shadowing. Then, a novel hybrid supervised pre-training network is proposed to expand the integration of global features within Masked Autoencoders (MAE) by incorporating a parallel classification branch. It can effectively enhance the feature capture capabilities by integrating global features and local details. Besides, the newly designed losses are proposed to strengthen the training efficiency and improve the learning capacity, based on reconstruction loss and classification loss.ConclusionsExtensive experiments are performed on our dataset as well as the public dataset. Experimental results demonstrate that our method achieves the best performance among the state-of-the-art methods, highlighting the advantages of efficient implementation of plant technology and having good prospects for real-world applications.

S[formula omitted]: Self-supervised learning with sparse-dense sampling

Self-supervised visual representation learning (SSL) attempts to extract significant features from unlabeled datasets, alleviating the necessity for labor-intensive and time-consuming manual labeling processes. However, existing contrastive learning-based methods typically suffer from the underutilization of datasets, consume significant computational resources, and employ longer training epochs or large batch sizes. In this study, we propose a novel method aimed at optimizing self-supervised learning that integrates the advantages of sparse-dense sampling and collaborative optimization, thereby significantly improving the performance of downstream tasks. Specifically, sparse-dense sampling primarily focuses on high-level semantic features, while leveraging the spatial structure relationship provided by the unlabeled dataset to ensure the incorporation of low-level texture features to improve data utilization. Besides, collaborative optimization, including contrastive and location tasks, further enhances the model’s ability to perceive features of different dimensions, thereby improving its utilization of features in the embedding space. Furthermore, the combination of sparse-dense sampling and collaborative optimization strategies can reduce computational consumption while improving performance. Extensive experiments demonstrate that the proposed method effectively reduces the computational requirements while delivering favorable results. The codes and model weights will be available at https://github.com/AI-TYQ/S4.

Enriching Education with Artificial Intelligence Generative Ai-Speech to Image Generator

Abstract: Visual memory is the strongest in learning; It is 60,000 times more powerful than text and memory. This important fact shows that there is an urgent need to make changes in the education process, moving away from old, monotonous practices and towards a dynamic, effective and permanent educational support. Inspired by the effectiveness of the invisible aspects of visual learning, this article introduces GenClassroom, a new learning tool that promises to revolutionize the traditional teaching method. GenClassroom uses the power of artificial intelligence (AI) to translate and transform teacher lessons into beautiful images, providing students with a unique learning experience beyond the boundaries of the classroom environment. Seamlessly integrating speech-to-image capabilities into dynamic virtual classroom environments, GenClassroom enables educators to create engaging, interactive lessons that resonate with students and promote understanding, retention, and engagement. Through a qualitative study of GenClassroom’s design, functionality, and application content, this article outlines the evolution of the vision of AI-enabled education to shape the future of learning. As the ed- ucational landscape changes dramatically, GenClassroom serves as a beacon of innovation, ushering in a new era of personalized, meaningful, and empowering learning. By embracing the endless possibilities of visual learning enhanced by artificial intelligence, GenClassroom paves the way for a future where learning has no boundaries and every student can reach their potential.

From land to water: “Sunken” T-maze for associated learning in cichlid fish

The study introduced and evaluated learning paradigms for Maylandia callainos cichlids using a modified version of the rodent T-maze, filled with tank water (the "sunken" modification). Both male and female fish underwent training in two distinct conditioning paradigms. Firstly, simple operant conditioning involved placing a food reward in either the right or left compartment. Cichlids demonstrated the ability to purposefully find the bait within 6 days of training, with a persistent place preference lasting up to 6 days. Additionally, the learning dynamics varied with sex: female cichlids exhibited reduction in latency to visit the target compartment and consume the bait, along with a decrease in the number of errors 3 and 4 days earlier than males, respectively. Secondly, visually-cued operant conditioning was conducted, with a food reward exclusively placed in the yellow compartment, randomly positioned on the left or right side of the maze during each training session. Visual learning persisted for 10 days until reaction time improvement plateaued. Color preference disappeared after 4 consecutive check-ups, with no sex-related interference. For further validation of visually-cued operant conditioning paradigm, drugs MK-801 (dizocilpine) and caffeine, known to affect performance in learning tasks, were administered intraperitoneally. Chronic MK-801 (0.17 mg/kg) impaired maze learning, resulting in no color preference development. Conversely, caffeine administration enhanced test performance, increasing precision in fish. This developed paradigm offers a viable approach for studying learning and memory and presents an effective alternative to rodent-based drug screening tools, exhibiting good face and predictive validity.

The Faces and Forms of Pandemic Humor: Exploring Covid-19 Memes with Visual Machine Learning

The Covid-19 pandemic brought about an unprecedented cycle of digitally spread humor. This article analyzes a corpus of 12,337 humor items from 80+ countries, mainly in visual format, and mostly memes, collected during the first half of 2020, to understand the features and intended audiences of this “pandemic humor”. Employing visual machine-learning techniques and additional qualitative analysis, we ask which actors and which templates were most prominent in the pandemic humor, and how these actors and templates vary on the following dimensions: local vs. global, Covid-specific vs. general, and specifically for the actors, political vs. not political. Our analysis shows that most pandemic memes from the first wave are not political. The vast majority of the memes are global: They are based on well-recognized meme templates, and almost all identified actors are part of a cast of set “meme faces”, mostly from the US and the UK but recognized around the world. Most popular templates were found in several countries and languages, including non-European languages. Most memes were based on non-Covid specific templates, but we found new Covid-specific memes, which sheds new light on the process by which memes emerge, spread, and potentially become new meme templates. Our analysis supplements existing studies of (Covid) memes that mostly focus on small national samples, using qualitative methods. This cross-national analysis is enabled by a global dataset with unique data on geographical origin of humor. We show the usefulness of visual machine learning for identifying the emergence, spread and prevalence of transnational (humorous) cultural forms. By combining large-scale computational analysis with in-depth analysis, we bridge a gap in in meme studies between (mostly quantitative) data sciences and (mostly qualitative) communication and media studies.

Metabolic Syndrome Status Changes and Cognitive Functioning: Insights from the Lifelines Cohort Study

BackgroundMetabolic syndrome is associated with increased risk of dementia. Yet, findings on how longitudinal development of metabolic syndrome status affects cognition remain controversial.ObjectivesThis study examines whether individuals with different changes in metabolic syndrome status differ in cognitive functioning. Additionally, the prevalence of metabolic syndrome within the Lifelines population-based study is investigated.Design14609 Lifelines participants (mean age 60.8, 56.4% women) were divided into four groups based on their metabolic syndrome status changes between 2007–2013 (1) and between 2014–2017 (2): without metabolic syndrome (N=10863; absent at 1 and 2), de novo metabolic syndrome (N=1340; absent at 1 and present at 2), remitting metabolic syndrome (N=825; present at 1 and absent at 2), and persistent metabolic syndrome (N=1581; present at 1 and 2). ANCOVA models were employed to assess group differences in psychomotor function, visual attention, visual learning, and working memory assessed using the Cogstate Brief Battery.ResultsAccounting for education, age, sex, and time between examinations, groups did not statistically differ in any of the four cognitive outcomes. The prevalence of metabolic syndrome within the Lifelines population increased with age and differed among men and women.ConclusionPerformance in psychomotor function, visual attention, visual learning, and working memory measured by the Cogstate Brief Battery did not differ between individuals with different changes in metabolic syndrome. The length of metabolic syndrome exposure was unknown, making our results exploratory and calling for future studies addressing this gap.

Why do individuals with Williams syndrome or Down syndrome fail the Weather Prediction Task?

Williams syndrome (WS) and Down syndrome (DS) are two neurodevelopmental disorders with distinct genetic origins characterized by mild to moderate intellectual disability. Individuals with WS or DS exhibit impaired hippocampus-dependent place learning and enhanced striatum-dependent spatial response learning. Here, we used the Weather Prediction Task (WPT), which can be solved using hippocampus- or striatum-dependent learning strategies, to determine whether individuals with WS or DS exhibit similar profiles outside the spatial domain. Only 10% of individuals with WS or DS solved the WPT. We further assessed whether a concurrent memory task could promote reliance on procedural learning to solve the WPT in individuals with WS but found that the concurrent task did not improve performance. To understand how the probabilistic cue-outcome associations influences WPT performance, and whether individuals with WS or DS can ignore distractors, we assessed performance using a visual learning task with differing reward contingencies, and a modified WPT with unpredictive cues. Both probabilistic feedback and distractors negatively impacted the performance of individuals with WS or DS. These findings are consistent with deficits in hippocampus-dependent learning and executive functions, and reveal the importance of congruent feedback and the minimization of distractors to optimize learning in these two populations.

Analysis of Students' Mathematical Concept Understanding Ability on Circle Material Based on Learning Style

This research aims to analyze students' mathematical concept understanding ability in solving circle material problems by considering learning styles. The method used in this research is qualitative method with descriptive approach. This research was conducted on students of class XI Culinary 1 at SMKN 6 Semarang which amounted to 36 students. Data were collected through mathematical concept understanding test and student learning style questionnaire. The subjects in this study were three students who represented each student's learning style. The techniques used to collect data were observation, mathematical concept understanding ability test, interview and documentation. The results showed variations in learning styles and variations in students' mathematical concept understanding abilities in solving circle material problems. Learners with visual and auditory learning styles tend to have better understanding abilities in solving the problem, while learners with kinesthetic styles show different patterns. So it can be concluded that the learning style of learners can affect students' mathematical understanding ability in solving circle material problems, therefore the importance of recognizing the learning style of students in the mathematics learning process. Each learner with a different learning style has a different mathematical concept understanding ability, so an approach that is in accordance with the characteristics of learners is needed to improve students' mathematical concept understanding ability.

Somatic, Auditory, Visual, Intellectual Learning Model in Improving Vowel Pronunciation for 3rd Class Deaf Students

The ability to pronounce vowels in deaf students is still low, the indications are the occurrence of replacement, addition, and even the omission of phonemes. On the other hand, there is the unpreparedness of the teacher in setting the right model and method during articulation exercises, ignoring the basic receptive and expressive language skills of deaf students, allegedly as a form of teacher failure in practicing articulation both during individual and classical learning. For this reason, it is necessary to have a learning model that can accommodate the needs of deaf students to articulate correctly. This study aims to determine the effectiveness of the SAVI (Somatic Auditory Visual Intellectual) learning model in improving the pronunciation of vowels in class III deaf students. The approach used in this research is quantitative with the type of experimental research in the form of SSR (Single Subject Research) with ABA design. Data was collected using Observation and Treatment Tests carried out on one deaf child. The results of the study were that in the baseline-1 condition, the intervention increased by a value of 73.33, the intervention in Baseline-2 decreased by a value of 60.83, and although the intervention in Baseline-2 experienced a decrease, the data obtained was much better than the baseline-1, which was 26.66. In conclusion, the Somatic, Auditory, Visual, and Intellectual learning model affects improving the pronunciation of vowels in Deaf Students. For this reason, teachers must pay attention to and develop sensory modalities in deaf students in an integrated and holistic way in learning articulation.