October, 2023
Accepted Papers in October, 2023
◇Takashi Date, Mariko Sasakura, Kenichi Iwata, Masakazu Nakamoto, Toshiki Hino, Kazuhiko Nishi:Effectiveness of Body Movements to Enjoy Online Classes
◇Jun Iio:An Evaluation of the Flipped Classroom Approach Toward Programming Education
◇Jaana Helena Holvikivi:A Risk Evaluation Framework for Digitalization of Education with an Emphasis on Africa
◇Minae Nishimoto, Keiji Emi:Text Mining Analysis of What Students Think About e-learning and face-to-face Class on Account of COVID-19
◇Sayaka Tohyama, Yoshiaki Matsuzawa, Takito Totsuka:What is the consequence of attaining a greater sense of empowerment? – longitudinal cohort study of early programming education in Japan during the ’80s and ’90s –
◇Ben Wada:Teaching Computer Science Unplugged in Online for Undergraduate College Students
◇Yutaro Ohashi:Changes in information and communication technology use and programming education in Japanese elementary schools between 2017 and 2022
◇Kimio Kuramitsu, Momoka Obara, Miyu Sato, Yuka Akinobu:Training AI Model that Suggests Python Code from Student Requests in Natural Language
◇Yuko Murakami, Yukari Sho, Tomohiro Inagaki:Improving motivation in learning AI for undergraduate students by case study
◇Yui Ono, Daisuke Saito, Hironori Washizaki, Yoshiaki Fukazawa:Measuring Complexity in Visual Programming for Elementary School Students
◇Maiko Shimabuku, Yuzuru Aoki, Susumu Kanemune:School-wide Programming Education in a Public Elementary School
◇Hideki Kondo, Sayaka Tohyama, Ayano Ohsaki, Masayuki Yamada:Time-shifting Method to Mitigate Discussion Stagnation and Promote SNS Collaboration
◇Tomonari Kishimoto, Yuki Honda, Kosuke Urushihara, Maiko Shimabuku, Susumu Kanemune:Connect DB: An Online Learning System for Data Analysis
◇Toru Ochi, Koji Tateno:Efficacy Comparison of Online Classes in the Real-time Setting with ones in the On-demand Viewing Model
◇Hiroki Yasui, Takahiro Inoue, Takayuki Sasaki, Rui Tanabe, Katsunari Yoshioka, Tsutomu Matsumoto:SPOT: In-depth Analysis of IoT Ransomware Attacks using Bare Metal NAS Devices
◇Kosei Takashima, Isao Yagi:Model building and description using the agent-based computational economics framework for accounting
◇Hyuga Matsuo, Katsuhide Fujita:Effective Acceptance Strategy using Deep Reinforcement Learning in Bilateral Multi-issue Negotiation
◇Kouhei Kita, Ryuya Uda:Fast Preprocessing by Suffix Arrays for Managing Byte n-grams to Detect Malware Subspecies by Machine Learning
◇Zhou pei, Hiroyuki Shinnou, Hirotaka Tanaka:Combining Generative Model and Attention Network for Anomaly Detection