Academic literature on the topic 'Multiple Intelligence; Learning Style; Academic'
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Journal articles on the topic "Multiple Intelligence; Learning Style; Academic"
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Jeevitha.S and Mrs.Vanitha.J. "A STUDY OF MULTIPLE INTELLIGENCE IN RELATING TO LEARNING STYLE AMONG HIGHER SECONDARY STUDENTS." International Journal of Research - Granthaalayah 5, no. 6 (2017): 310–19. https://doi.org/10.5281/zenodo.821037.
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Students’ reveal different learning styles and multiple intelligences, and only by accommodating these several abilities can teachers appropriately plan and conduct tasks and evaluate what students have learned. The present study describes the types of learning styles and multiple intelligences of students, as well as instructional methods that work best with students’ relevant learning traits. The main motive is to study on multiple intelligence in relating to learning style among higher secondary students in Coimbatore district. This research is under taken with a view to examining the relationship with multiple intelligence and learning style of different high school students with a sample size 300. The investigation is analyzed by the descriptive analysis and differential analysis. The result concluded from the study that there is no substantial change with respect to gender, locality, groups and board of institution in their mean score of multiple intelligence and learning style. The correlation is not significant with the multiple intelligence and learning style.
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Budhathoki, Bamita, Poojan Sharma, Indira Adhikari Poudel, Dikshya Niraula, and Anita Sharma. "Multiple Intelligence Among Health Professionals Students in Selected Health Science Institute, Kathmandu." Journal of Manmohan Memorial Institute of Health Sciences 10, no. 1 (2025): 5–8. https://doi.org/10.3126/jmmihs.v10i1.77687.
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Introduction: Health professionals’ education often uses traditional teaching methods like lectures, which may not meet the diverse learning needs of students. Gardner’s Theory of Multiple Intelligences highlights nine types of intelligence that affect how students learn. This study aims to analyze of multiple intelligence among Health professional students. Method: A descriptive cross-sectional design was carried out among 275 student in Manmohan Memorial Institute of Health Sciences, Kathmandu using non-probability purposive sampling technique. Data was collected through self-administered questionnaire technique by using Gardner’s Multiple Intelligence Test and VAK learning styles model and analyzed by descriptive and inferential statistics using SPSS 25. Ethical approval was taken from NECHO IRC. Results: Bodily-kinesthetic intelligence had the highest mean score (6.0), followed by naturalist intelligence (5.8). Female students scored highest in kinesthetic learning style (10.2) and bodily-kinesthetic intelligence (6.0) but lowest in linguistic, spatial, and musical intelligence (4.9). Bachelor of Pharmacy students had the highest visual learning style score (10.7), while BSc Nursing students had the lowest linguistic intelligence score (4.4). Intrapersonal intelligence negatively correlated with visual learning style (r = -0.161, P = 0.006) and positively with kinesthetic learning style (r = 0.213, P = 0.001). Age had positive correlation with linguistic (r = 0.139, P = 0.025), bodily-kinesthetic (r = 0.151, P = 0.015), interpersonal (r = 0.239, P = 0.000), and naturalist intelligence (r = 0.212, P = 0.001). Among females, kinesthetic learning style positively correlated with intrapersonal intelligence (r = 0.256, P = 0.000), whereas in males, spatial intelligence negatively correlated with auditory learning style (r = -0.266, P = 0.050). Conclusion: Bodily-kinesthetic and naturalist intelligences were the highest among students, with distinct gender and program-specific variations in learning styles and intelligences. Significant correlations between learning styles, intelligences, and demographic factors suggest the need for tailored teaching approaches.. Thus, Educators should adopt multimodal teaching strategies that align with diverse learning styles and intelligences to enhance academic outcomes.
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Jahanian Najafabadi, Amir, Hadis Imani, Reza Beygi, António Mendes Lopes, and Lucas Filipe Martins Da Silva. "Intelligence, Beliefs on IQ and Learning Style predict Academic Performance in Mechanical Engineering Students." U.Porto Journal of Engineering 8, no. 1 (2022): 59–72. http://dx.doi.org/10.24840/2183-6493_008.001_0007.
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In this study we aimed to investigate whether beliefs on intelligence, intelligence quotient, and learning styles predict academic performance among students in mechanical engineering. For this purpose, forty-two students from the Department of Mechanical Engineering of the University of Porto were recruited among the available population. Participants responded to the measurement of this study via a Google form and on a voluntary basis. To investigate our hypothesis, beliefs on intelligence inventory, learning style questionnaire, Raven’s Progressive Matrices IQ test and their GPA as an indicator of their academic performance were used. Correlation analysis revealed significant effects between reflector learning style and academic achievement. Multiple regression also revealed a significant main effect of the reflector learning style on academic performance (p = .044). This study further revealed no significant correlation between other learning styles, beliefs on intelligence, intelligence quotient and academic performance.
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Ray, Suvendu, Mousumi Halder, and Deb Prasad Sikdar. "Nature of Multiple Intelligences and Perceptual Learning Styles of Prospective Teachers in West Bengal, India." International Journal of Research and Review 10, no. 10 (2023): 137–43. http://dx.doi.org/10.52403/ijrr.20231018.
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In light of the students' various learning styles and levels of intelligence, different pupils learn in different ways. This study analyses the multiple intelligences and learning styles of 410 prospective teachers from teacher training institutes in West Bengal, India. During the data collection procedure, researchers used a random sampling technique. It indicates that there are differences between women and men in particular forms of intelligence (spatial, musical, interpersonal, and intrapersonal), which tend to be disregarded in our conventional teacher education programmes. The verbal-linguistic, logical-mathematical, and bodily-kinesthetic categories of intelligence—which are frequently acquired through curriculum—do not exhibit statistically significant gender differences. The sensation-intuition dimension is the only one where there are gender differences in learning style. The sole conclusion that can be drawn from these findings is that prospective teachers' preferred learning styles are merely disregarded during the teaching-learning process, which should include techniques for nurturing them. The findings of this study imply that incorporating teaching methods that take into account multiple intelligences and learning styles may have a positive impact on students' academic performance. Comparably, while deciding which students to accept for a given course, academic institutions must take multiple intelligences into consideration as well. Keywords: Multiple Intelligences, Learning Styles, Prospective Teachers
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Yavich, Roman, and Irina Rotnitsky. "Multiple Intelligences and Success in School Studies." International Journal of Higher Education 9, no. 6 (2020): 107. http://dx.doi.org/10.5430/ijhe.v9n6p107.
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The applications of multiple intelligence theory in education are wide. Students apply the learning in the classroom according to their own dominant intelligence and learning style, which is most effective for them. Combining learning styles with dominant intelligences enhances the students' learning processes.The purpose of this case study is to examine the relationship between dominant intelligences according to Gardner's multiple intelligence theory and middle school students' academic achievement. A case study was conducted in Israel, in a middle school, among seventh-graders and involved 158 students.Findings indicated that in excellent classes - 80.9% of students had logical intelligence, in at least one of the levels of dominance; in ordinary classes only 48.4% of students have logical intelligence, at least in one of the levels of dominance. We also examined the relationship between the amount of dominant intelligences among students in all classes, excellent and ordinary. Findings indicated that in excellent classes the percentage of students with two or three dominant intelligences was higher than the percentage in ordinary classes. It is important to note that these are not just the logical and verbal, but also all types of intelligences, such as spatial, musical, kinetic and others.In conclusion, the dominant intelligences that highly influence and measure achievement in the education system are not the logical-mathematical and the linguistic-verbal, but the only logical-mathematical. Moreover, the amount of intelligences at the dominant levels can predict and indicate student's success at school.
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Katowa-Mukwato, Patricia, Fabian Chapima, Brenda Nambala-Sianchapa, and Victoria Mwiinga-Kalusopa. "Learning styles and intelligence types versus academic performance of nursing students of the University of Zambia." Journal of Nursing Education and Practice 7, no. 10 (2017): 83. http://dx.doi.org/10.5430/jnep.v7n10p83.
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Background: Learning styles are inherent personal attributes that determine the preferred teaching and learning method(s) for individual while an intelligence type is an individual’s levels of aptitude in various content areas as there is no one individual who is universally intelligent. An understanding of the two concepts is essential for designing suitable teaching approaches.Methods: This was a descriptive correlation study which explored the relationship between two variables; learning styles and intelligence types and academic performance of nursing students enrolled in the conventional nursing program at the University of Zambia. Data on learning styles was collected using the Visual, Auditory, Reading/Writing and Kinesthetic (VARK) questionnaire version 7.8 as proposed by Neil Fleming while Gardner’s questionnaire for assessing multiple intelligences was used to collect data on the students’ intelligence types. Results for the end of 2015/2016 academic year were used to determine academic performance.Results: Almost two thirds 64 (65.4%) of the participants’ academic performance was at credit level, 32 (32.7%) were at pass while only 2 (2%) were meritorious students. Participants had wide-ranging learning styles from unimodal, to bimodal and tri modal styles, although the majority were unimodal learners 81 (82.6%). Among the unimodal learners, majority 35 (35.5%) were kinaesthetic. On the other hand, 37 (37.8%) had logical mathematical intelligence, followed by bodily-Kinaesthetic 27 (27.6%). Both learning styles and intelligence types showed negative correlation and no significant association with academic performance. The Pearson r correlation and level of significance between learning styles and academic performance was -.092 and 0.372 respectively, while that for intelligence types and academic performance were -.027 and 0.790. Of the three demographic variables of age, gender and year of study, only age showed a positive correlation and significant association with academic performance (p = .002, and r = .144).Conclusions: The negative correlation between learning styles and intelligence types and academic performance may be an indication that the teaching methods utilized for nursing students are varied and therefore capable of promoting learning across different styles and intelligence types without necessarily favouring a specific style or type or that there is simply no association between learning styles and intelligence types and academic performance.
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Khanal, Saroj. "Determinants of Academic Performance of BBA Students: A Case of Pokhara University Affiliated Colleges." Nepalese Journal of Management 11, no. 3 (2024): 194–209. https://doi.org/10.3126/njm.v11i3.79618.
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This study examines the determinants of academic performance a case of BBA students of Pokhara University. Academic performance is the dependent variable. The selected independent variables are intelligence and cognitive abilities, motivation and self efficiency, learning style and strategies, emotional intelligence and well-beings, and time management. The primary source of data is used to assess the opinions of respondents regarding intelligence and cognitive abilities, motivation and self-efficiency, learning style and strategies, emotional intelligence and well-beings, and time management. The study is based on primary data of 131 respondents. To achieve the purpose of the study, structured questionnaire is prepared. The correlation and multiple regression models are estimated to test the significance and importance of determinants of academic performance of BBA students: A case of Pokhara University affiliated colleges. The study showed a positive impact of intelligence and cognitive abilities on academic performance. It indicates that increasing cognitive abilities of student leads to increase academic performance. Similarly, the study showed a positive impact of motivation and self efficiency on academic performance. It indicates that higher motivation leads to increase academic performance. Likewise, the study also revealed a positive impact of learning style and strategies on academic performance. It indicates that effective learning style and strategies leads to increase academic performance. Further, the study observed a positive impact of emotional intelligence and well-beings on academic performance. It indicates that emotionally stability leads to increase academic performance. In addition, the study observed a positive impact of time management and study habits on academic performance. It implies that effective time management increase academic performance.
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Macalangcom, Ainah, and Junge Guillena. "Multiple Intelligences, Perceived Teaching Styles, and Academic Performance of Junior High School Students." Psychology and Education: A Multidisciplinary Journal 26, no. 9 (2024): 977–93. https://doi.org/10.5281/zenodo.13957113.
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This study explored the relationship between multiple intelligences and academic performance among Junior high school students at Al-Hamlan National High School during the Academic Year 2023-2024. Employing a descriptive-correlational research design, respondents were selected via simple random sampling to ensure a representative sample from the entire population. Results unveiled sex as a notable predictor, with females demonstrating higher academic achievement compared to males. Furthermore, parental education levels emerged as influential factors, with children of college-educated parents exhibiting lower academic performance. However, demographic variables like age group, along with teaching styles and various types of multiple intelligences, failed to significantly predict academic outcomes. The findings underscored the necessity of integrating diverse teaching methodologies and recognizing individual cognitive strengths in educational practices. By considering the multifaceted nature of intelligence and its impact on academic success, educators could tailor their approaches to better meet the diverse needs of students, thereby fostering a more inclusive and effective learning environment.
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Nugroho, Bangkit Indarmawan, Nugroho Adhi Santoso, and Aang Alim Murtopo. "Prediksi Kemampuan Akademik Mahasiswa dengan Metode Support Vector Machine." remik 7, no. 1 (2023): 177–88. http://dx.doi.org/10.33395/remik.v7i1.12010.
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Indikator yang digunakan untuk mengukur keberhasilan pelaksanaan pendidikan di perguruan tinggi adalah kinerja/kemampuan akademik (academic performance) mahasiswa, yang dapat diukur dari prestasi akademik (academic achievement) mahasiswa yaitu berdasarkan capaian nilai (grade), yang di Indonesia disebut dengan IPK (Indeks Prestasi Kumulatif). Penelitian ini bertujuan untuk membuat sebuah pemodelan dengan menggunakan metode support vector machine untuk mengklasifikasikan dan memprediksi kemampuan akademik mahasiswa berdasarkan faktor demografi, multiple intelligence, dan learning style yang ia miliki.Metode support vector machine memiliki karakteristik khusus yaitu berusaha mencari hyperplane terbaik (maximal margin hyperplane) yang berfungsi sebagai pemisah dua buah class pada input space. Proses klasifikasi dilakukan dengan cara melakukan pembelajaran terhadap data training. Pada kenyataannya, dataset hampir selalu bersifat nonlinear, sehingga dalam proses pembelajaran data training memerlukan fungsi kernel. Hasil pembelajaran kemudian diujikan ke dalam data uji sehingga bisa menghasilkan nilai akurasi. Dalam penelitian ini digunakan fungsi kernel polynomial ordinal-2, dan hasil yang diperoleh menghasilkan nilai akurasi yang cukup tinggi yaitu 92.5% yang menunjukkan hubungan yang signifikan antara faktor demografi, multiple intelligence, dan learning style terhadap kemampuan akademik mahasiswa yang diklasifikasikan ke dalam dua kelas, potensial dan tidak potensial. Hasil lainnya menunjukkan bahwa di antara ketiga faktor tersebut, faktor multiple intelligence memiliki tingkat signifikansi tertinggi terhadap kemampuan mahasiswa
 
 Kata Kunci: support vector machine, demografi, multiple intelligence, learning style, fungsi kernel
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Prihartini, Dyah. "HUBUNGAN GAYA BELAJAR DAN INTELEGENSI DENGAN HASIL BELAJAR KIMIA SISWA KELAS XI IPA MAN 1 SAMARINDA." Jurnal Ilmiah Widya Borneo 6, no. 2 (2024): 169–77. http://dx.doi.org/10.56266/widyaborneo.v6i2.146.
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This study is aimed to determine the relationship between learning styles and intelligences with learning outcomes chemistry class XI IPA at MAN 1 Samarinda. This research is quantitative research. The research methodology used in this study is a quantitative survey research method with correlation approach.
 This research, which acts as the sample is whole class XI IPA MAN 1 Samarinda Academic Year 2020/2021, total number is 107 students. The research instrument used to collect data for the learning styles questionnaire in the form of sheet, the data intelligence was required from IQ test results of students (IQ test instrument: progressive matrices) while learning outcome data of value semester exam results of academic year 2019. Data analysis was conducted to determine how strong the relationship between learning styles and intelligences with learning outcomes chemistry class XI IPA.
 Based on the research results, it is showing a positive relationship between learning style with chemistry student learning outcomes, the partial correlation coefficient of 0.102 (do very low), the coefficient of determination (p Y12) = 0.017, meaning that 1.7% of variance results of studying chemistry (Y ) can be explained by chemistry learning styles (X1) via regression y = 65.880 + 0.062 X1. Sedaang 98.3% variation in chemistry learning outcomes (Y) caused by other factors. There is a positive relationship between intelligence with chemistry student learning outcomes, the partial correlation coefficient of 0.301 (low relationship), the coefficient of determination (p Y12) = 0.096, meaning that 9.6% of variance results of studying chemistry (Y) can be explained by the learning styles chemistry (X1) via regression Y = 51.877 + 0.188 X2. While 90.4% of the variation of chemical learning outcomes (Y) caused by other factors.
 There is a positive relationship between learning styles and intelligence together with chemistry student learning outcomes, the partial correlation coefficient (R) of 0.325 (low relationship), (R2) coefficient of determination (p Y12) = 0.106 (10.6% ). This means that 10.6% of the studied chemistry class XI Science MAN 1 Samarinda influenced by the styles of learning and intelligence while the remaining 89.4% is influenced by other factors. This relationship is expressed by multiple linear regression Y = 46.654 + 0,047 X1 + 0,182 X2.
 Key words : Learning Styles, Intelligence, Learning Outcomes
Dissertations / Theses on the topic "Multiple Intelligence; Learning Style; Academic"
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Combs, Daniel Paul. "PREDICTING LICENSING EXAMINATION PERFORMANCE WITH COGNITIVE STYLE AND REACTIVE BEHAVIOR PATTERN ASSESSMENTS." Doctoral diss., University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4494.
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Candidates for Florida real estate sales associate licensure responded to a two-part questionnaire based on William A. Long's Reactive Behavior Patterns Theory and Robert J. Sternberg's Triarchic Theory of Intelligence. Examination scores were converted to a dichotomous pass/fail variable based on the Florida Real Estate Commission-mandated cut-off score of 75 correctly answered questions out of 100. The candidates' responses to the questionnaire comprising the Long-Dziuban Inventory and the Cognitive Strengths Task List based on Sternberg's theory, were crosstabulated with pass/fail to identify differential passing proportions, if any, based on reactive behavior pattern and/or cognitive strength. An ANOVA procedure was used with the raw scores to determine whether statistically significant differences in mean exam scores existed between the four Long Types and the three Cognitive Types adapted from Sternberg's theory. The data were subjected to similar analyses to ascertain whether the ancillary traits described by Long were predictive of exam performance. A crosstabulation of Long Type by Cognitive (Sternberg) Type was performed to find out if any significant relationships existed between the several dimensions of the Long-Dziuban Inventory and the Cognitive Strengths Task List. The results revealed a moderate statistically significant relationship between exam performance and cognitive strength, with analytical types and creative types having the greatest exam success. Tenuous relationships were identified between exam performance and the Long types and traits and between the Long-based and the Sternberg-based components of the research instrument. Although the results of this study did not establish definitive relationships between the Long and Sternberg constructs, by combining them into a measure of cognitive style, it forged a framework for future research into the relationship between licensing examination performance and cognitive styles. Within this framework are the components of a predictive model potentially useful for identifying not only real estate licensing exam performance but also for identifying persons likely to succeed in the real estate industry.<br>Ph.D.<br>Department of Educational Research, Technology and Leadership<br>Education<br>Educational Research, Technology, and Leadership
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Horvath, Judith A. "A Multiple Online Learning Platform Study of the Impact of Learning Style on Academic Performance." NSUWorks, 2003. http://nsuworks.nova.edu/gscis_etd/590.
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This research study investigated the relationship between learning style and academic achievement on multiple online learning platforms. The study was based upon data gathered from students enrolled in online courses at two community colleges in northeastern Pennsylvania. The study utilized the theoretical model of David Kolb's learning style theory, the Kolb Learning Style Instrument (LS13), and a researcher-developed survey. Students volunteering to participate in the study completed the survey and LSI. The learning styles, as identified by David Kolb include: accommodator, assimilator, converge, and diverge. These learning styles were compared to the students' academic performance in the courses. The students' academic achievement was measured by their final course grade. The learning styles and academic achievement of the students were statistically analyzed and correlated to the online learning style platform the colleges utilized. The online learning platforms in this study are the two most widely utilized (Blackboard (Bb) and WebCT).
Descriptive statistics and inferential statistical methods were utilized to test the hypotheses related to this research study. The ANOV A and t-test were two of the methods used to test the interval data. The results of the study suggest there were no statistically significant differences related to achievement based upon learning styles on the Bb platform and the WebCT platform. In addition, there were no statistically significant differences in achievement between the Bb platform and the WebCT platform.
There were also, no statistically significant differences in achievement between the learning styles on the Bb platform or on the WebCT platform. The research study also developed a learning style student profile for the Bb platform and the WebCT platform based upon the results of the statistical analysis and random sample population statistics. Data collected from the researcher-developed survey provided information related to age, gender, prior online course experience, prior computer experience, type of course enrolled in, major course of study, family income level, employment status, and the influence of use of multimedia on academic performance. Males and females were represented in all learning style categories with the exception of the diverger learning style category. There were no male divergers on either the Bb platform or the WebCT platform. Although these variables identified were not the major thrust of this research study, they provided insight into future research studies to be undertaken.
This study expected to find differences based upon course platform and/or learning style, however due to some limitations of the study, no significant differences were found. That is not to say differences are not there, just they were not uncovered by this particular piece of research. The results of the study may not be generalized to the entire learning community nationwide based upon the investigation being conducted only on two community colleges in the northeastern section of Pennsylvania and using only two online learning platforms. Additional studies are recommended to further test the hypotheses using different additional online learning platforms, larger sample sizes, and extend findings with other university populations.
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Wang, Shu-Fen, and 王淑芬. "A Study of the Relationship Between Learning Style and Multiple Intelligence in Elementary Students." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/61197951981539445726.
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碩士<br>國立屏東師範學院<br>數理教育研究所<br>91<br>Both of grade 4 and grade 6 students（about 638 students）in Kaohsiung City, were the targets in this study. Survey and correlation methods were adopted in this study. There are three main purposes to be discussed in this study. First, comparing these students in varieties of background （gender and grade） distinguish between learning style and multiple intelligence. Secondly, to discuss the different learning style that are left brain learning style, right brain learning style, and integrated learning style in multiple intelligence in elementary students. Finally, it can be used to discuss the relationship between learning style and multiple intelligence in elementary students.
The tools of this study include “Form of Learning Style”, ”Form of Multiple Intelligence.” The data of this study describes statistics, one-way MANOVA and typical relationship and so on to use it.
The findings of the study are：
1.On learning style, the distribution showed significant tend to integrated learning style in Kaohsiung elementary students.
2.On multiple intelligence, the elementary students in Kaohsiung City the scores is higher than the mean value. Bodily-kinesthetic was generally superior, while naturalist intelligence inferior.
3.With reference to the different sexes, having been showed significant differences in the Learning Style Appraisal, and female students were significantly superior to male students.
4.With reference to the different sexes, have been showed significant differences in the Multiple Intelligence Appraisal score. Female students were significantly superior to male students on certain kinds of intelligence such as linguistic intelligence, musical intelligence, interpersonal intelligence, and intrapersonal intelligence in the Multiple Intelligence Appraisal score.
5. In Kaohsiung City, both of grade 4 and grade 6 elementary students races did not show any significant difference in the Learning Style Appraisal.
6.With reference to the different grades, both of grade 4 and grade 6 elementary students of Kaohsiung City have showed significant differences in the Multiple Intelligence Appraisal score. Grade 4 students were significantly superior to grade 6 students on certain kinds of intelligence such as logical-mathematical intelligence, linguistic intelligence, patial intelligence, musical intelligence, intrapersonal intelligence, and naturalist intelligence in the Multiple Intelligence Appraisal score.
7.The elementary students who have different learning styles showed significant differences in the Multiple Intelligence Appraisal score.
8.As to the relation of the learning style and multiple intelligence, the higher the elementary students of right brain learning styles and the integrated learning styles , the better of linguistic intelligence , patial intelligence, and intrapersonal intelligence. And the higher the elementary students of left brain learning styles, the better of musical intelligence and naturalist intelligence .
Finally, based on the findings of this study, the researcher proposed some suggestions for educational applications and future studies.
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Jaeger, Audrey J. Bess James L. "Emotional intelligence, learning style, and academic performance of graduate students in professional schools of public administration." Diss., 2001. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3004907.
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Chu, TsungWen, and 鞠宗紋. "The Effectiveness of Applying Pictures for Language Learning Based on Multiple Intelligence and Learning Style of Children with Disabilities." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/07780183861106527958.
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碩士<br>國立臺中教育大學<br>幼兒教育學系碩士班<br>100<br>Picture books were widely used to improve pre-school children’s language ability, but not often for children with disabilities. In order to raise the language abilities of these children, the researcher designed a picture teaching method which included a set of simple–drawing pictures, as well as a series of short story pictures.
This study attempted to analyze the effects of applying pictures for language learning. Two pre-school children with disabilities participated in this experimental study for four months. The independent variable was the teaching method involving the application of pictures. The dependent variable was the language ability of the children in this study. In this program, there were a total of 37 pictures and 12 story books to be used for each child. The child had 220 minutes per week to learn language through the picture teaching method. The researcher then carried out multiple assessments of language learning ability with various testing tools. Their parents and researcher also periodically had to fill out the check lists of multiple intelligence and learning style. The results of this study were as follows:
1.These two children had their own individual superior intelligence and learning styles. The performances of superior intelligence and learning style were consistent with each other.
2.This picture teaching method was compatible with the requirements of spatial intelligence and sensation preference.
3.For these two children, the simple topic story books designed by the researcher were more attractive than colorful story books published commercially.
4.The results, through the application of the triangulation method, indicated that the picture teaching method can enhance both the language understanding skills and oral expression of these two children.
5.Picture teaching methods could enhance children’s cognitive ability.
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Hsiao, Hui-wen, and 蕭惠雯. "The Effects of Integrating the Theory of Multiple Intelligences into Junior High School English Instruction on Academic Achievement of Students with Various Learning Styles." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/40848483920715378191.
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碩士<br>明道大學<br>教學藝術研究所<br>94<br>The Effects of Integrating the Theory of Multiple Intelligences into Junior High School English Instruction on Academic Achievement of Students with Various Learning Styles
Advisor：Yu-Liang Chang, Ph.D.
Author： Hui-wen Hsiao
Abstract
In recent years, the double-curve phenomenon of English learning became the key issue of current reform movement in junior high school English education. Even though facing students with various learning styles, the teaching model used in the traditional education tended to be unitary. The unified schedule progress and general instructional principles were still a common status in all settings. Further, every student’s unique personality would be omitted as well as one’s special needs based on a specific learning style. It would be also improbable to reach the goal of enhancing students’ academic achievement. Accordingly, the purpose of this study was to integrate the theory of Multiple Intelligences (MI) into junior high school English instruction and to investigate the effects on academic achievement of students with various learning styles.
A quasi-experimental design was employed in this study. Seventy-five eighth graders totally selected purposefully from one junior high school will participate in this study. Students from two different classes were divided into two groups：the experimental group and the control group. Reliable and valid questionnaires were used to verify the status of students’ various learning styles and multiple intelligences. According to the distribution of students’ multiple intelligences, a series of instructional activities integrating MI were designed for the experimental period of ten weeks. Only the experimental group received the treatment. The average of scores of nine English academic examinations collected from the past three semesters were considered as the performance of the pre-test, while the score of the mid-term academic examination as the post-test. Data gathered were analyzed by ANCOVA to explore the effects of integrating MI into English instruction on academic achievement of students with various learning styles.
The main findings were reported as followings: There was no statistically significant difference on learning styles between male and female students, however according to brain-based researches, males and females might have some constitutional differences. Therefore, they might have great differences in behavior and ways of thinking. Moreover, though the academic achievement of both groups had no statistically significant difference between the pre-test and post-test, the learning motivation and atmosphere in the experimental group were much better than the controlled group. These findings revealed that English instruction integrating with MI could improve students’ learning motivation and help students learn through one another. And even though the academic achievement of all learning styles in the experimental group had no significant difference between the pre-test and post-test, students with individual learning style particularly showed a greater improvement than those of other learning styles. Also, since the number of students with individual learning style was the least (i.e. only two students), it would be so important that students could be cultivated to possess the ability of studying independently. Further, since adding audiovisuals to the instructional processes would stimulate students’ learning, teachers might provide more flash cards, pictures, music and chant as teaching aids.
In addition, the qualitative data collected by classroom observations and instructional notes were analyzed integratedly with the quantitative data for the purpose of completeness. Based on research findings, recommendations were finally provided for the improvement of students’ future learning achievement and the English instruction.
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江達隆. "The study on the influence of multiple intelligence,learning style, learning motivation and learning strategy upon the vocational high school students’ learning effectiveness." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/73701624060497242855.
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博士<br>國立彰化師範大學<br>工業教育與技術學系<br>96<br>This research explores the interplay among multiple intelligence, learning styles, learning motivations, and learning strategies toward learning effectiveness for vocational high school students. The researcher has reviewed related literature and has constructed a theoretical framework for the study. In the process of obtaining experimental data, the subjects involved in the study were selected by the stratified cluster sampling method. Thirty-one vocational high schools were selected, and 2,474 participants were included in the field investigation. After careful evaluation, 2,128 of the total 2,474 questionnaires were responded; that is, the available returned rate was 91%. The data were analyzed to test the hypothesis by using statistical procedures: frequency distribution, percentage, t-test, one-way ANOVA, point biserial correlations, Pearson product moment correlations, and path analysis statistical methods. It was expected that the result could be used as practical implications for promoting the instructional effectiveness of vocational high school teachers.
The conclusions of this research are listed as follows:
1.Math-logical intelligence performance of vocational high school boy students are significantly higher than that of girl students, and the linguistic intelligence performance of vocational high school girl students are significantly higher than boy students’ performance.
2.Linguistic and logical-mathematical intelligence performance of public vocational high school students or students from families of high social-economical status are significantly higher than that of private or students from families of low social-economical status.
3.Math-logical intelligence performance of vocational high school industrial program students are significantly higher than that of linguistic program students, and linguistic intelligence performance of linguistic program students are significantly higher than industrial program student’s performance.
4.Vocational high school boy students are significantly more active and sensational in learning styles than girl students, while vocational high school girl students are significantly more reflective and intuitive in leaning styles than boy students.
5.There are more sequential learners among public vocational high school students than among private vocational high school students.
6.Vocational high school girl students show more value judgments and emotional concerns than boy students in their leaning motivations.
7.Vocational high school students from families of high social-economical status show more expectancy components than those from families of low social-economical status.
8.Vocational high school students in northern, central and eastern parts of Taiwan show more value judgments and emotional concerns in their learning motivations than those in southern Taiwan.
9.Vocational high school girl students, public high school students and vocational high school students in central Taiwan perform significantly better in their cognitive strategies, metacognitive strategies and resource management strategies than vocational high school boy students, and private vocational high school students as well as vocational high school students in Southern Taiwan.
10.Vocational high school students from families of high social-economical status utilize metacognitive strategies more frequently, while those from families of low social-economical status utilize cognitive strategies more often.
11.Vocational high school students’ intrapersonal intelligence of multiple intelligences is significantly correlated with judgment components and expectancy components involved in learning motivations.
12.Vocational high school students’ linguistic and musical intelligence of multiple intelligences are significantly correlated with cognitive strategies in learning motivations, while musical intelligence and intrapersonal intelligence of multiple intelligences are moderately correlated with resource management strategies in learning motivations.
13.Learning effectiveness can be predicted by studying multiple intelligences and learning strategies of vocational high school students.
According to the results described above, the research hereby provides the following recommendations for the promotion of learning effectiveness in vocational high schools and related further studies.
1.Adequate career planning should be provided based on the difference of multiple intelligences between vocational high school boy and girl students.
2.Basic learning competency of private vocational high school students should be reinforced to increase their learning effectiveness.
3.Intrapersonal intelligence of vocational high school students should be further cultivated to upgrade their learning motivation.
4.Learning skills of students from families of low social-economical status should be sharpened to raise their learning effectiveness.
5.Learning styles of vocational high school students should be taking into consideration so as to provide proper learning surroundings for individual students.
6.Students should be enlightened to understand the value and future development of attending vocational high schools and to meet their learning satisfaction.
7.The cause of low learning motivation of some vocational high school students should be probed into so as to work out some remediable strategies.
8.Vocational high school boy students as well as private vocational high school students should be given some available learning strategies to raise their learning satisfaction.
9.Multiple instructional strategies should be exploited to promote the learning results of vocation high school students.
10.Teaching and practical apparatus of vocational high schools should replenished to raise learning effectiveness.
11.Learning ineffectiveness in vocational high schools of southern Taiwan should be examined and discussed to work out adequate effective measures.
Key words: Multiple Intelligence, Learning Style, Learning Motivation, Learning Strategy, Learning Effectiveness
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Lin, Chiu-Ping, and 林秋萍. "A Study on the Multiple Intelligence and Learning Style of Junior High School Students in the Five Central Counties of Taiwan." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/13618915464253217257.
Full textAbstract:
碩士<br>國立彰化師範大學<br>教育研究所<br>96<br>The purpose of this study is to investigate the relationship between multiple intelligence and learning style for junior high school students. Research instrument include multiple intelligence scale and Kolb’s learning style inventory. By using stratified random sampling method, a total of 1,099 junior high school students in central Taiwan were selected to participate in the study. The applied analysis methods are descriptive statistics, t test, factor analysis, Pearson product-moment correlation, one-way ANOVA and liner regression analysis.
Students with various backgrounds have significant differences in part of the multiple intelligences and learning style orientation. The strength intelligence for the junior high school students is music intelligence, and the weakness intelligence is naturalist intelligence. The students’ preferences for learning styles are diverger, accommodator, assimilator, and converger in priority. In addition, there is significant relationship between learning style orientation and part of the multiple intelligences. Finally, based on the results of this study, there are some suggestions offered.
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Chen, Ming-huei, and 陳明輝. "The Effect of Applying Multiple Intelligence Theory to Vocational High School English Teaching on Students’ Learning Motivation and Academic Achievement." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/16380843402727327824.
Full textAbstract:
碩士<br>國立臺中教育大學<br>教育學系課程與教學碩士班<br>101<br>This study aimed to discuss the effect of applying multiple intelligence theory to vocational high school English teaching on students’ learning motivation and academic achievement.
This experiment adopted quasi-experimental design and used one vocational high school class totaling 42 students in Chunghua county as subjects. The experimental period of this study was about eight weeks and many statistical methods, such as pair T-test and one-factor ANCOVA, were used to test the research hypothesis. Besides, self-made English Learning Motivation Test, Academic Achievement Test and Class Chemistry Test were utilized as research tools. The conclusion was listed below：
1. Applying multiple intelligence theory to vocational high school English teaching is statistically significant on students’ learning motivation.
2. Applying multiple intelligence theory to vocational high school English teaching is non-significantly different on students’ learning motivation of different genders.
3. Applying multiple intelligence theory to vocational high school English teaching is non-significantly different on students’ academic achievement.
4. Applying multiple intelligence theory to vocational high school English teaching is non-significantly different on students’ learning motivation of different genders.
Last, according to the research results, this study provided concrete suggestions for teachers, schools and further study in the future.
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Lin, Chiu Lin, and 林秋伶. "A Study on the Correlation between Multiple Intelligence and Learning Style of Students of Music Class in Primary and Secondary School in Miaoli." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/3h6k4a.
Full textAbstract:
碩士<br>國立臺北藝術大學<br>藝術與人文教育研究所<br>100<br>This study aimed to investigate the public primary and secondary school students of music class multiple intelligence and learning style, and both the current situation with the difference between background variables, and analysis of their mutual relations.The research method used questionnaires and the preparation of "Miaoli County Junior High School students of music class relationship between multiple intelligence and learning style questionnaire" for the county of Miaoli County 247 public primary and secondary school students of music class established for the survey. Statistical analysis methods were used to process questionnaire data and applied to research data include descriptive statistics, factor analysis, reliability analysis , independent sample t-test, one-way ANOVA(analysis of variance) and Pearson-Moment correlation .The findings of this study are as follows:
1. The students of music class in secondary school in
Miaoli,they aware their multiple intelligence and
learning style are in good condition.
2. The students of music class in secondary school in
Miaoli,multiple intelligence was found to be influenced
differently by gender ,grade, majoring in musical
instruments category , years of music studying and
school location.
3. The students of music class in secondary school in
Miaoli , learning style was found to be influenced
differently by grade, majoring in musical instruments
category , years of music studying and school location.
4. In general, there is a significant positive correlation
between multiple Intelligence and learning style.
According to the above conclusions,the researcher will provide some suggestions for government educational institutions, schools and researchers, in the future.
Books on the topic "Multiple Intelligence; Learning Style; Academic"
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Zwiers, Jeff. Developing Academic Thinking Skills in Grades 6-12: A Handbook of Multiple Intelligence Activities. International Reading Association, 2004.
Find full textBook chapters on the topic "Multiple Intelligence; Learning Style; Academic"
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Kassem, Youssef, Hüseyin Çamur, and Mohamed Almojtba Hamid Ali Abdalla. "Predicting the Mechanical Power of a New-Style Savonius Wind Turbine Using Machine Learning Techniques and Multiple Linear Regression: Comparative Study." In 11th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence - ICSCCW-2021. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92127-9_44.
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Planells-Artigot, Enrique, Santiago Moll-Lopez, and Adolfo Nuñez-Perez. "Conversations with a Purpose: The Impact of ChatGPT Among Higher Education Students." In European Higher Education Area 2030: Bridging Realities for Tomorrow’s Higher Education. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-75140-0_29.
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Abstract Artificial intelligence (AI) tools are reshaping the educational landscape. Multiple international organisations are alerting about the benefits as well as risks associated with the deployment of this technology. Large Language Models (LLMs) like ChatGPT, a conversational AI, emerge as a notable player, offering dynamic interactions with humans. This study focuses on how this tool challenges traditional learning paradigms and how students use ChatGPT to obtain information. This study seeks to understand the extent and nature of ChatGPT's use in academic contexts based on a survey of under- and postgraduate students (n = 1,372 students) in Spain from different areas of knowledge. The questionnaire evaluates the frequency of ChatGPT usage in various academic activities, including homework, classroom interactions, and knowledge reinforcement. At the same time, students were asked how much they rely on the results obtained from the AI. The responses illustrate the moderate level of trust in ChatGPT as well as the different uses depending on the academic disciplines. The study offers revealing results on how students reflect on their own learning process, the future of education, and the role of instructors along their academic progress. A significant finding underscores ChatGPT's rise as the primary educational information source, surpassing long-established mediums like textbooks and online resources. Additionally, videos maintain a robust position as a secondary source of information. This research casts light on the shifting preferences and trends in modern educational tools, underscoring the pivotal role of AI-driven platforms in today's academic endeavours.
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Statti, Aubrey L. C., and Kelly M. Torres. "Multiple Intelligence Theory in the Digital Age of Learning." In Examining Multiple Intelligences and Digital Technologies for Enhanced Learning Opportunities. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0249-5.ch001.
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The understanding of how individuals learn is continually changing. With the tremendous influence of technology in the classroom, it is vital that educators integrate the use of technology with specific attention and profound thought with respect to the needs of learners, including the role of multiple intelligences. Moreover, learning environments are now customizable due to new communication and information technology tools that are revolutionizing education. Research indicates the need to coordinate the use of technology with the style in which students learn. With the tremendous options and continual transformations available, educators must appraise instructional techniques, specifically the use of technology, with consideration to various learning styles and intelligences in order to engage students in their learning and also to reinforce learning in various ways. This article seeks to explore the concepts of multiple intelligence theory through technology applications.
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Neo, Tse-Kian, and Sahar Sabbaghan. "The Impact of the Relationship between Gardner's Multiple Intelligence and Kolb's Learning Style." In Knowledge Discovery, Transfer, and Management in the Information Age. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4711-4.ch009.
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In a diverse work environment, it is important to have diverse leaders, managers, and people with different talents and intelligence in order to deal with different problems. In this case, each individual can know their own strength and weakness, and know which position works best for them. The concept of learning styles is used to describe individual differences in the way people learn. According to Kolb (1984), each person has a unique way to absorb and process experiences and information. He has identified four statistically prevalent learning styles- diverging, assimilating, converging, and accommodating. On the other hand, Gardner's Multiple Intelligence Theory is very helpful to recognize that people have differing aptitude in different subject areas. This chapter documents a study in which the participants consisted of 153 bachelor students of Management from the Multimedia University of Malaysia. They were given two questionnaires, one for Kolb's learning style and other for Gardner's Multiple Intelligence inventory and a correlation was conducted. The results showed that there was a significant relationship between Kolb's Learning Style and Multiple Intelligence. The relationship could be seen particularly in Abstract Conceptualization (AC) and Multiple Intelligences which were Nature, kinesthetic, music, word, interpersonal, and picture. The results also indicated that the majority of the participants are between AC and AE which means they are convergers. Having the right information for companies can be beneficial since knowing how their employees learn can lead to a diverse workplace that would have significant results on organizational structure, planning, development, and operation.
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Goletsis, Y., C. Papaloukas, Th Exarhos, and C. D. Katsis. "Bankruptcy Prediction through Artificial Intelligence." In Machine Learning. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch320.
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Bankruptcy prediction or corporate failure is considered a classic issue in both, academic and business communities. Bankruptcy risk is one of the most important factors (if not the most important one) to be considered when credit requests are screened or even existing debtors are evaluated. On the other hand, all potential stakeholders (shareholders, suppliers, customers, employees, creditors, auditors, etc.) have potential interest to identify if a company is on a trajectory that is tending towards failure. Commercial banks, public accounting firms and other institutional entities (e.g., bond rating agencies) appear to be the primary beneficiaries of accurate bankruptcy prediction, since they can use research results to minimize exposure to potential client failures. In addition to avoiding potentially troubled obligors, the research can also benefit in other ways. It can help in accurately assessing the credit risk of bank loan portfolios. Credit risk has been the subject of much research activity, since the regulators are acknowledging the need and are urging the banks to assess the credit risk in their portfolios. Measuring the credit risk accurately also allows banks to engineer future lending transactions, so as to achieve targeted return/risk characteristics. The other benefit of the prediction of bankruptcies is for accounting firms. If an accounting firm audits a potentially troubled firm, and misses giving a warning signal then it faces costly lawsuits (Atiya, 2001). A series of techniques have been applied in literature. Econometric / statistical methods have first appeared in literature: In late 1960’s (multiple) discriminant analysis (DA) was the dominant method; during the 1980’s logistic analysis. In the 1990’s artificial intelligence starts appearing in financial literature with neural networks (Odom & Sharda 1990) serving as an alternative to statistical methods demonstrating promising results. The goal of this chapter is therefore two-fold: First, it intends to give an overview of the artificial intelligence techniques successfully applied to the problem, ranging from the first neural network applications to recent applications of biologically inspired algorithms, such as genetic algorithms. Then, two kernel based methods, namely the Radial Basis Function Neural Networks and the Support Vector Machines are applied to the bankruptcy problem.
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Mahajan, Vaishali, and Meena Kumari R. "Impact of Artificial Intelligence on Education." In Advances in Educational Technologies and Instructional Design. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-6170-2.ch002.
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Technology has become an integral part of the present time. Advancements in technology have drastically changed the working, learning, and interaction style of the people. With the help of innovations, life became easier and faster. Artificial intelligence (AI), a recent development, has caught the attention of people by its capacity to work like humans. Although there are various advantages of AI in education, but it is not free from adverse effects on learning. It was observed that AI may encourage dishonesty and jeopardize academic integrity. The main goals of the chapter are to highlight the benefits and drawbacks of artificial intelligence in education. The chapter will highlight AI's continued significance in education.
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McDermott, Brenda. "AI as an Accessibility Tool." In Academic Integrity in the Age of Artificial Intelligence. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-0240-8.ch009.
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While generative AI is often discussed in terms of challenging notions of academic integrity, it is increasingly looked at as a potential tool to break down barriers in post-secondary education. In particular, this chapter considers how generative artificial intelligence technologies could be leveraged to provide multiple means of engagement, representation and expression (CAST, n.d.). In other words, how can the use of generative AI support social justice in higher education. An ethical approach to generative AI requires respect for the diversity among learners. An ethical approach to generative AI must reflect fairness, which requires recognizing the inherent biases built into the post-secondary learning environments. Using generative AI to support universal design for learning shifts this narrative, considering how technology acceptance could support social justice in post-secondary learning.
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Pye, Michael. "Buddhist-style Pilgrimage with Shinto Meanings." In Exploring Shinto. Equinox Publishing, 2020. http://dx.doi.org/10.1558/equinox.39489.
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Circulatory pilgrimage to multiple sites (o-meguri お巡り) was first developed in Japan in the context of Buddhist devotions, notably at 33 sites in western Japan dedicated to the Bodhisattva Kannon. In Japanese Buddhist Pilgrimage (Pye 2015) it was shown how the idea of o-meguri was transferred to the context of Shintō, partly due to the popularity of the intermediate Seven Gods of Good Fortune. In this paper two leading cases of circulatory pilgrimage within the Shinto world are explored: one around 25 places where reverence is paid to the god of learning, Sugawara Michizane, concluding with Kitano Tenmangū in Kyoto, and the other which includes no less than 125 sites at Ise. Neither of these pilgrimages bears any Buddhist meaning. The Michizane shrines provide a religious focusing of scholastic or academic ambition. At Ise the main point lies in the purification of the individual’s heart or mind, and in the strengthening of one’s identity in a shared national orientation. The older idea of o-Ise-mairi remains relevant in so far as visits to these many sites are all regarded as referring to one single goal, the Jingū.
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Ghule, Gauri, Snehal Rahul Rathi, Niraj Diwan, and Pratham Katariya. "Transforming Academic Emotion Analysis With Integrating Deep and Machine Learning Models." In Modern Digital Approaches to Care Technologies for Individuals With Disabilities. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7560-0.ch008.
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The prediction of academic emotions in learning environments, like engagement, confusion, or boredom, is done using machines in this chapter. By capturing physiological signals, facial expressions, and interaction patterns from multiple sensors, this work seeks to create predictive models that can identify and quantify students' emotion states during learning processes. Pre-developed models use artificial intelligence machine learning techniques to analyze faces and predict emotion in real time using videos or pictures extracted from the stream. The description focuses on preprocessing data first, extracting features representing students' emotions, and then training different models using them. By automating the means of emotion recognition, the processors help educators understand emotions and use the burst of time to address learner's needs.
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Glotova, Galina Anatolevna. "The study of the relationship between the motives of learning with self-regulation and student academic performance." In Theoretical and practical aspects of pedagogy and psychology. Publishing house Sreda, 2024. http://dx.doi.org/10.31483/r-112449.
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The study is devoted to the analysis of the relationship between the motives of learning, measured by two methods based on different theoretical approaches, with the main regulatory processes (planning, modeling, programming, evaluation of results) and regulatory and personal properties (flexibility, independence), as well as with students' self-reports on academic performance. The study used the following methods: «Diagnostics of students' learning motivation» (Badmaeva, 2004), «Scales of academic motivation» (Gordeeva, Sychev, Osin, 2014), «Style of self-regulation of behavior – SSP-98» (Morosanova, 2000) and self-report of students on their academic performance over the past semesters. The study was conducted using an online survey in a Google form on a sample of 82 university students aged 18–29 years. Correlation analysis (according to Spearman) and factor analysis (with Varimax rotation) were used in data processing. The results of the study: multiple significant correlations of learning motives, measured by two different methods «Diagnostics of student learning motivation» and «Scales of academic motivation», with scales of the SSP-98 methodology were obtained; significant positive correlations of learning motives with self-report on academic performance allow us to analyze the types of students' activities that include learning activities, that requires the use of already developed educational technologies and the development of new ones in the educational process at the university.
Conference papers on the topic "Multiple Intelligence; Learning Style; Academic"
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Maulany, Gerzon Jokomen, Paulus Insap Santosa, and Indriana Hidayah. "Multiple Intelligence Learning Style Detection in E-learning using Support Vector Machine (SVM) Algorithm." In 2024 7th International Conference on Informatics and Computational Sciences (ICICoS). IEEE, 2024. http://dx.doi.org/10.1109/icicos62600.2024.10636915.
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Yi, Xiaoyuan, Zhenghao Liu, Wenhao Li, and Maosong Sun. "Text Style Transfer via Learning Style Instance Supported Latent Space." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/526.
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Text style transfer pursues altering the style of a sentence while remaining its main content unchanged. Due to the lack of parallel corpora, most recent work focuses on unsupervised methods and has achieved noticeable progress. Nonetheless, the intractability of completely disentangling content from style for text leads to a contradiction of content preservation and style transfer accuracy. To address this problem, we propose a style instance supported method, StyIns. Instead of representing styles with embeddings or latent variables learned from single sentences, our model leverages the generative flow technique to extract underlying stylistic properties from multiple instances of each style, which form a more discriminative and expressive latent style space. By combining such a space with the attention-based structure, our model can better maintain the content and simultaneously achieve high transfer accuracy. Furthermore, the proposed method can be flexibly extended to semi-supervised learning so as to utilize available limited paired data. Experiments on three transfer tasks, sentiment modification, formality rephrasing, and poeticness generation, show that StyIns obtains a better balance between content and style, outperforming several recent baselines.
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Nojima, Yusuke, Kazuhiro Watanabe, and Hisao Ishibuchi. "Variants of heuristic rule generation from multiple patterns in Michigan-style fuzzy genetics-based machine learning." In 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI). IEEE, 2015. http://dx.doi.org/10.1109/taai.2015.7407091.
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"Study Of Suitable Learning Methods Based on Multiple Intelligence on Agricultural Waste Management Course’s Students in Polytechnic Kota Bharu." In 2nd International Conference on Frontiers in Academic Research ICFAR 2023. All Sciences Academy, 2023. http://dx.doi.org/10.59287/as-proceedings.447.
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Williams, Jennifer. "End-to-End Signal Factorization for Speech: Identity, Content, and Style." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/746.
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Preliminary experiments in this dissertation show that it is possible to factorize specific types of information from the speech signal in an abstract embedding space using machine learning. This information includes characteristics of the recording environment, speaking style, and speech quality. Based on these findings, a new technique is proposed to factorize multiple types of information from the speech signal simultaneously using a combination of state-of-the-art machine learning methods for speech processing. Successful speech signal factorization will lead to advances across many speech technologies, including improved speaker identification, detection of speech audio deep fakes, and controllable expression in speech synthesis.
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Ye, Yutong, Yingbo Zhou, Jiepin Ding, Ting Wang, Mingsong Chen, and Xiang Lian. "InitLight: Initial Model Generation for Traffic Signal Control Using Adversarial Inverse Reinforcement Learning." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/550.
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Due to repetitive trial-and-error style interactions between agents and a fixed traffic environment during the policy learning, existing Reinforcement Learning (RL)-based Traffic Signal Control (TSC) methods greatly suffer from long RL training time and poor adaptability of RL agents to other complex traffic environments. To address these problems, we propose a novel Adversarial Inverse Reinforcement Learning (AIRL)-based pre-training method named InitLight, which enables effective initial model generation for TSC agents. Unlike traditional RL-based TSC approaches that train a large number of agents simultaneously for a specific multi-intersection environment, InitLight pre-trains only one single initial model based on multiple single-intersection environments together with their expert trajectories. Since the reward function learned by InitLight can recover ground-truth TSC rewards for different intersections at optimality, the pre-trained agent can be deployed at intersections of any traffic environments as initial models to accelerate subsequent overall global RL training. Comprehensive experimental results show that, the initial model generated by InitLight can not only significantly accelerate the convergence with much fewer episodes, but also own superior generalization ability to accommodate various kinds of complex traffic environments.
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Stolić, Predrag, Zoran Jovanović, Sonja Jovanović, Željko Mravik, Marija Grujičić, and Marko Jelić. "IMPROVING THE QUALITY OF PRACTICAL TEACHING BY APPLYING ELEMENTS OF MACHINE LEARNING AND PREDICTIVE ANALYTICS." In 1st International Scientific Conference Education and Artificial Intelligence. University of Niš, Pedagogical Faculty, Vranje, 2025. https://doi.org/10.46793/edai24.129s.
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The standard practice in calculation and laboratory exercises often involves students working with the same dataset. While this simplifies the process, it also creates a significant opportunity for academic dishonesty, such as plagiarism, as students may resort to using others’ work or results. This undermines the intended learning outcomes. Additionally, there is tendency of the use of measurement data from real world which presents some challenges, particularly in terms of providing a large volume of diverse datasets due to limitations in time, funding, resources, and the accuracy and repeatability of measurements. This paper introduces a new approach that leverages machine learning and predictive analytics to address these issues. Starting with an initial real dataset obtained through experimental methods, different models are used to predict results, generating new synthetic datasets for educational purposes. By varying the models and their parameters, multiple versions of the data are created, ensuring that smaller student groups receive identical datasets for their tasks, while in some cases, each student may be assigned a unique dataset. The paper also has an evaluation of the results achieved through this approach in teaching both basic and master’s level courses in a one technical faculty’s study program.
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Longe, Olumide, Sharma Navel, Julius Amedgadzie, Christabel Acquaye, and Deborah Kanubala. "The Future is Intelligent: Empowering Future Ready Workforce Through Artificial Intelligence (AI) Education At The Academic City University College Accra Ghana." In 28th iSTEAMS Multidisciplinary Research Conference AIUWA The Gambia. Society for Multidisciplinary and Advanced Research Techniques - Creative Research Publishers, 2021. http://dx.doi.org/10.22624/aims/isteams-2021/v28p8.
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With the current advancements of automation and robotics, it is expected that AI is going to transform the global economy in an exponential manner. To leverage the new opportunities, there is a need for preparation as well as learning and developing new skills for those new jobs. It is in this regard that Academic City is taking the AI agenda into the forefront, nurturing and empowering the African student to lead the continent into the new AI era. Academic City University College (ACity) is set to lead the sub-region in technology and innovation education with the introduction of an undergraduate degree in Artificial Intelligence (AI). The university becomes the first in Africa to offer a degree in AI. The program, which has commenced already forms part of the university’s short-term effort to develop a cadence of new programs that will invariably push the boundaries of knowledge while establishing a foothold for successful graduates in the jobs of the future. This paper projects the innovative attempt at addressing the manpower challenges in Artificial Intelligence by ACity, Accra, Ghana and her pioneering efforts in the West African sub-region that led to the launch of a new Bachelors Programme in Artificial Intelligence. The programme style and curriculum are presented while also providing perspectives on how the programme fits into the global and African quest to develop skills and strategies to upscale technological advancement as we face an intelligence-driven future. Keywords — ACity, Artificial Intelligence (AI), Robotics, BSc, Ghana, Degree, Education, University, UNESCO
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Longe, O. B., N. Sharma, J. Amegadzie, C. Acquaye, and D. Kanubala. "The Future is Intelligent: Empowering Future Ready Workforce Through Artificial Intelligence (AI) Education At The Academic City University College Accra Ghana." In 28th iSTEAMS Multidisciplinary Research Conference AIUWA The Gambia. Society for Multidisciplinary and Advanced Research Techniques - Creative Research Publishers, 2021. http://dx.doi.org/10.22624/aims/isteams-2021/v28p8xx.
Full textAbstract:
With the current advancements of automation and robotics, it is expected that AI is going to transform the global economy in an exponential manner. To leverage the new opportunities, there is a need for preparation as well as learning and developing new skills for those new jobs. It is in this regard that Academic City is taking the AI agenda into the forefront, nurturing and empowering the African student to lead the continent into the new AI era. Academic City University College (ACity) is set to lead the sub-region in technology and innovation education with the introduction of an undergraduate degree in Artificial Intelligence (AI). The university becomes the first in Africa to offer a degree in AI. The program, which has commenced already forms part of the university’s short-term effort to develop a cadence of new programs that will invariably push the boundaries of knowledge while establishing a foothold for successful graduates in the jobs of the future. This paper projects the innovative attempt at addressing the manpower challenges in Artificial Intelligence by ACity, Accra, Ghana and her pioneering efforts in the West African sub-region that led to the launch of a new Bachelors Programme in Artificial Intelligence. The programme style and curriculum are presented while also providing perspectives on how the programme fits into the global and African quest to develop skills and strategies to upscale technological advancement as we face an intelligence-driven future. Keywords — ACity, Artificial Intelligence (AI), Robotics, BSc, Ghana, Degree, Education, University, UNESCO
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Bagiati, Aikaterini, Andrés Felipe Salazar Gómez, John Radovan, Kathleen Kennedy, and Cynthia Breazeal. "Learning journeys for scalable AI education: an MIT - USAF collaboration." In SEFI 50th Annual conference of The European Society for Engineering Education. Universitat Politècnica de Catalunya, 2022. http://dx.doi.org/10.5821/conference-9788412322262.1189.
Full textAbstract:
In 2021 the United States Air Force (USAF) and the Department of Defence (DoD) entered into a collaboration with multiple units within the Massachusetts Institute of Technology (MIT) to develop a new academic program focusing on Artificial Intelligence (AI) training. Given the size and the diversity within the body of USAF employees, the goal of this collaboration is to design and implement an innovative program that will achieve maximum learning outcomes at scale for learners with diverse roles and educational backgrounds. This program is now piloting and evaluating three different learning journeys addressing three different groups of USAF employees (USAF leaders and decision makers; technology developers; and daily frontend technology users). The learning journeys were designed based on each group’s specific professional needs and academic backgrounds, and they include combinations of online synchronous and asynchronous courses and face-to-face activities. The program’s pilot is currently underway and evaluation research findings are informing the next program iterations. The ultimate goal of this program is to formulate general recommendations on how to serve large numbers of diverse learners at scale in an optimum way. In addition to an evaluation pilot study, MIT experts on AI and the Science of Learning have been asked to review the program and their feedback will be integrated into the next program iteration. This paper presents the three learning journeys as originally designed to serve the three first diverse cohorts of learners, as well as the plan for future improvement and implementation of the program.