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 relat
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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 qu
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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 indic
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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-lin
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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
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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
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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.
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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 e
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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
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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 tes
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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 identi
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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, conv
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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. Final
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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 teachi
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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 ins
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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
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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.

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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 vari
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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.

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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
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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.

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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 establish
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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.

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Book 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 &amp; 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.
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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 gene
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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
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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
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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 repeat
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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 undergrad
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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.

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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 undergrad
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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.

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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 j
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