Impact of Information Communication Technology Strategies on Learning Effectiveness

Transnational higher education is a multinational growth strategy requiring a foreign direct investment to establish a university or a campus in a new country and, if possible, to use articulation agreements with credible partners to increase domestic enrolment. Due to the potential international student learning style differences, we hypothesized there may be difficulties teaching Information Communication Technology (ICT) courses in transnational strategies due to the student origin or domestic campus location. The purpose of this study was to examine if student learning was effective within ICT graduate courses at an accredited sub-Saharan Africa-based university implementing the transnational education strategy. We found student learning was effective, but paradoxically, some factors indicated unusual results. Learning impact was higher when students disregarded the learning objectives, which we were able to explain theoretically. Conversely, learning impact was higher for many students who avoided tutoring, which we also rationalized.

Artificial Intelligence Applications with e-Learning System for China’s Higher Education Platform

Artificial Intelligence (AI) assisted educational institutions extensively utilize electronic learning context to guarantee improved teaching and learning experiences accompanied by educational activities. E-learning or online learning plays a significant role in Chinese higher education. There is a challenge to implement e-learning in China’s higher education to improve course resources, student learning style prediction, teaching quality, and service support. Hence in this paper, Artificial Intelligence based Efficient E-learning Framework (AI-EELF) has been proposed to overcome the challenges faced by China’s higher education while implementing e-learning modules. The collected student data can be efficiently utilized and exploited to progress in an adaptive learning environment. The proposed AI-EELF method introduces multiple learning models to enhance teaching quality and predict the student learning style. The experimental results show that the proposed AI-EELF achieves high performance, prediction ratio in determining students’ learning style and improves teaching quality compared to other existing methods.

Analisis Kesulitan Siswa SMA dengan Gaya Belajar Visual dalam Menyelesaikan Soal HOTS

<p><em>The difficulties of student in solving HOTS problems are caused</em><em> by</em><em> some factors. One of them is student learning style. Student learning styles are divided </em><em>into three types, namely</em><em> visual, auditorial, and kinest</em><em>h</em><em>etic</em><em>s</em><em>. This research focuses on visual learning style. This research uses a qualitative method aiming to d</em><em>e</em><em>scribe the difficulties of student in solving HOTS mathematic problems by visual learning style. The subject was taken using snowball sampling and purposive sampling technique. The data collection techniques were questionnaire, test, interview, and note range. Analysis techniques used on in this research were data reduction, data display and conclusion drawing. The result of this research was student who had a visual learning style got difficulty in using concept at problem with C6 grade. That was because the students were not familiar with HOTS problems.</em><em></em></p>

ANALISIS MINAT BELAJAR DAN GAYA BELAJAR SELAMA PANDEMI COVID-19 SISWA KELAS V SDN 3 CIKEMBULAN KECAMATAN PEKUNCEN KABUPATEN BANYUMAS TAHUN AJARAN 2020/2021

<p><em>Studying from home during the Covid-19 pandemic is more effective if the teacher concerns the student’s interest in learning and learning styles. The study aimed to analyze student’s interest in learning and learning styles and to describe factors influencing interest in learning and learning styles to fifth grade students at SD Negeri 3 Cikembulan during the Covid-19 pandemic. It was qualitative with narrative design. Data collection techniques used observation, interviews, and document studies. The observed aspects about interest in learning were fondness, interest, and student involvement while about learning styles were visual auditory, and kinesthetic. It concludes that student’s interest in learning is sufficient. The dominant student learning style is visual. Factors influencing interest in learning include talent, discipline, curiosity, concentration, learning needs, family, motivation, school, mass media, and society while factors influencing learning style include physical conditions, psychology, fatigue, family, school, and society.</em></p>

A STUDY OF ESP STUDENTS LEARNING STYLE AT DAYANU IKHSANUDDIN UNIVERSITY

The title of this research is A study of ESP Students Learning Style at Dayanu Ikhsanuddin University. The objective of the research is find out the ESP student learning style to be informed to the lecturers in order to used the match teaching style with the students’ learning style, and also informed to the students about their learning style.This research applied descriptive method and percentage analysis to classify ESP students learning styles at Dayanu Ikhsanuddin University in academic year 2018/2019. The sample of this Research was 53 students that taken randomly from the population. The instrument of this Research was questionnaire. In analyzing the students’ responses, the writer implemented the Likers Scale and the descriptive statistics was analyzed by using SPSS 21. The result of the research showed that most of ESP Students’ Learning Style at Dayanu Ikhsanuddin University were major in field Dependence and Reflective learning style preference and only a few students applied Independence, Analytic, global, and Impulsive.

Designing an expert system for determining student learning styles using forward chaining in engineering education

Engineering education prepares its graduates able to work in the community and entrepreneurship, the quality of graduates is highly determined by the quality of the learning process is no exception for student learning styles. The purpose of this study was to describe the design of the expert system to determine the student learning style, the method used was forward chaining. The results of the design of this application have been able to diagnose student learning styles efficiently and provide the best solutions for their learning.

The Effect Of Student Learning Style Intervention On The Relationship Between Learning Motivation And Learning Style

Proses transfer ilmu dalam dunia Pendidikan tinggi, dengan adanya kampus merdeka, yang mana mahasiswa harus lebih aktif menjadi salah satu factor untuk mahasiswa dapat memaksimalkan semua kemampuan guna mendapatkan hasil yang terbaik, dengan menciptakan motivasi dan memaksimalkan gaya belajar. Penelitian ini dengan tiga variable, yaitu variable bebas adalah motivasi belajar, variable terikat adalah hasil beljar, dan variable intervening adalah gaya belajar. Penelitian ini menggunakan Teknik analisis jalur, guna melihat pengaruh secara langsung dan pengaruh secara tidak langsung. Dengan object penelitian adalah mahasiswa aktif. Hasil penelitian menunjukan secara parsial motivasi belajar dan gaya belajar memberikan pengaruh secarta signifikan terhadap hasil belajar mahasiswa, dan dalam pengaruh langsung dan tidak langsung yang dimiliki, didapatkan hasil bahwasannya pengaruh tidak langsung lebih baik, dengan kata lain motivasi belajar dalam mempengaruhi hasil belajar yang di intervensi oleh variable gaya belajar, memberikan hasil yang lebih baik.