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Catherine Ferguson; Margaret K. Merga – Australian Journal of Language and Literacy, 2021
Low literacy in adulthood can be a powerful barrier to opportunity. Our research explored how participation in a free adult literacy program that provides dyadic support can help participants to build confidence and meet their unique literacy goals. We conducted in-depth interviews with 15 randomly-selected adult literacy learners who participated…
Descriptors: Adult Education, Tutoring, Self Esteem, Educational Objectives

Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
Kudzayi Savious Tarisayi; Ronald Manhibi – Journal of Learning and Teaching in Digital Age, 2025
This paper critically examines the transformative potential of Artificial Intelligence (AI) in Zimbabwe's higher education system, focusing on how AI can enhance learning outcomes and optimize administrative processes. The study employs a qualitative research approach, gathering insights from key stakeholders in the educational sector to identify…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Higher Education
Mukesh Kumar Rohil; Saksham Mahajan; Trishna Paul – Education and Information Technologies, 2025
Intelligent Tutoring Systems (ITS) and Augmented Reality (AR) have become greatly popular in current scenario, especially for helping students in mastering difficult subjects through a variety of different methods with the implementation of smart algorithms. There are many papers in the current literature that discuss the ITS architecture and the…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Physical Environment, Simulated Environment
Sarah Rissler; Bryan Hurd; Emily McColgan; Laura Schilling; Vince Fillipp; Jennifer Schmidt-McCormack – Learning Assistance Review, 2025
This study demonstrates a holistic view into the structure of the Student Athlete Study Room Program, collecting and analyzing data from the student athletes who participated in the program, the peer tutors who facilitated the program, the athletic coaches who engaged with the program support, and the professional staff administrative oversight…
Descriptors: Student Athletes, Tutoring, Peer Teaching, Athletic Coaches
Hüseyin Ates – Education and Information Technologies, 2025
Integrating Augmented Reality (AR) technology into Intelligent Tutoring Systems (ITS) has the potential to enhance science education outcomes among middle school students. The purpose of this research was to determine the benefits of an ITS-AR system over traditional science teaching methods regarding science learning outcomes, motivation,…
Descriptors: Technology Integration, Technology Uses in Education, Intelligent Tutoring Systems, Science Education
Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
Schulz, Sandra; McLaren, Bruce M.; Pinkwart, Niels – International Journal of Artificial Intelligence in Education, 2023
This paper develops a method for the construction and evaluation of cognitive models to support students in their problem-solving skills during robotics in school, aiming to build a basis for an implementation of a tutoring system in the future. Two Wizard-of-Oz studies were conducted, one in the classroom and one in the lab. Based on the…
Descriptors: Cognitive Processes, Models, Intelligent Tutoring Systems, Robotics
Bauer, Thomas; Biehler, Rolf; Lankeit, Elisa – International Journal of Research in Undergraduate Mathematics Education, 2023
Peer Instruction, first introduced by Eric Mazur in the late '90s, is a method aiming at active student participation in lectures. It includes conceptual questions (so-called ConcepTests) presented to the students, who vote on answer alternatives presented to them and then discuss their answers in small groups. As professors have been reported to…
Descriptors: Undergraduate Students, Peer Teaching, Discussion, Tests
Kang, Jiwon; Kang, Chaewon; Yoon, Jeewoo; Ji, Houggeun; Li, Taihu; Moon, Hyunmi; Ko, Minsam; Han, Jinyoung – Education and Information Technologies, 2023
Recent technologies have extended opportunities for online dance learning by overcoming the limitations of space and time. However, dance teachers report that student-teacher interaction is more likely to be challenging in a distant and asynchronous learning environment than in a conventional dance class, such as a dance studio. To address this…
Descriptors: Educational Technology, Online Courses, Dance Education, Artificial Intelligence
NORC at the University of Chicago, 2023
This brief reports on findings and implications from an evaluation of the Saga Education Virtual Math Tutoring Program. Research has demonstrated that Saga provides an effective tutoring model when delivered in person. This research studied whether the program was also effective when delivered virtually. The findings reveal that, overall, students…
Descriptors: Tutoring, Electronic Learning, Program Evaluation, Mathematics
Jennifer M. Lennon – ProQuest LLC, 2023
Modern classrooms are increasingly diverse. Students vary in their academic abilities, personal interests, cultural and linguistic backgrounds, and previous experiences (Allen et al., 2013). To meet the varied needs of students, educators must adapt their instruction so all are able to find success. Modifying lesson plans and changing instruction…
Descriptors: Preservice Teachers, Lesson Plans, Reading Centers, Universities
Abas, Muhamad; Uge, Sarnely; Alwy, Auliya Rahmasari – Elementary School Forum (Mimbar Sekolah Dasar), 2023
Social science learning outcomes of students in elementary schools are a problem faced by teachers. Parental guidance at home is one of the influencing factors. The purpose of this study is to determine the relationship between parental tutoring and social studies learning outcomes of fourth-grade students of one public elementary school in…
Descriptors: Tutoring, Parent Participation, Social Studies, Elementary School Students
Rosmansyah, Yusep; Putro, Budi Laksono; Putri, Atina; Utomo, Nur Budi; Suhardi – Interactive Learning Environments, 2023
In this article, smart learning environment (SLE) is defined as a hybrid learning system that provides learners and other stakeholders with a joyful learning process while achieving learning outcomes as a result of the employed intelligent tools and techniques. From literature study, existing SLE models and frameworks are difficult to understand…
Descriptors: Electronic Learning, Artificial Intelligence, Educational Technology, Technology Uses in Education
Lechuga, Christopher G.; Doroudi, Shayan – International Journal of Artificial Intelligence in Education, 2023
Computer-assisted instructional programs such as intelligent tutoring systems are often used to support blended learning practices in K-12 education, as they aim to meet individual student needs with personalized instruction. While these systems have been shown to be effective under certain conditions, they can be difficult to integrate into…
Descriptors: Algorithms, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Ability Grouping