Grants and Awards

Call for Grants 2025

Call for Proposals

Submission of Research Grant Applications in the Field of Innovations in Learning Technologies for 2025

Since its establishment in 1974, the Open University has been committed to academic excellence and expanding access to higher education across Israeli society. These founding principles remain at the core of the OUI's mission, reflecting our belief in the potential of human capital in all its diversity, and in education as the foundation for improving lives.
The OUI offers more than degrees; it empowers individuals and contributes to a stronger, more inclusive Israel. Our impact unfolds through individual transformation—one student and one success story at a time.

Publication and Acknowledgments:

Researchers receiving the grant are expected to use their findings in academic research projects and publications. Publications should acknowledge the funding support, stating: "This research was supported by the Center for Innovations in Learning Technologies at the Open University of Israel." This acknowledgment should be included in published papers, conference presentations, or other research outputs.

The research grant will be awarded in two phases: the first half upon notification of approval, and the second half upon submission of the final research report.

Submission Guidelines:

Research proposals will be reviewed by the academic committee of the center. Proposals should be a maximum of three pages and include the following: background, literature review, research questions, research methods (up to 250 words), estimated budget, expected outcomes, references, and an estimated research timeline. The inclusion of a data collection and analysis section is highly recommended. Additionally, proposals must include a short CV of the researchers. Proposals will be submitted as a PDF document to the center's academic committee, including references, citations, and appendices.

Deadline for Submission:

Research proposals and inquiries should be sent via email to innovation@openu.ac.il by May 10, 2025, with "Research Proposal Submission" as the subject line.

Grant Period:

The research grant will be provided for up to 12 months. An interim report is required no later than 20 months after approval of the proposal. Researchers are invited to present their findings at a special research event hosted by the Center for Innovations in Learning Technologies at the Open University.

Grant Recipients 2024

Exploring the Impact of Chatbots on Problem-Solving, Abstraction Abilities, Affective Factors, and Student Approaches in High School Computer Science Education

Dr. Rinat Rosenberg-Kima and Dr. Mor Friedborn-Yasherim, Faculty of Education in Science and Technology Technion - Israel Institute of Technology

This research proposal delves into the impact of Chatbot interactions on high school students majoring in Computer Science (CS). The primary aim is to investigate how chatbot engagement affects students' problem-solving skills and abstract reasoning within computational problem solving contexts. The study will also examine the wider affective responses to Chatbot usage, assessing how these AI interfaces influence students' emotional responses to the CS curriculum. Amidst the growing infusion of artificial intelligence in education, it is critical to evaluate both the cognitive and emotional repercussions. This is particularly relevant for optimizing student interactions with AI tools during key educational stages. Utilizing a mixed-methods approach, this investigation will dissect the complex role of Chatbots as educational tools. It aims to determine their potential to transform educational outcomes while dealing with problem-solving and developing thinking strategies and to influence self-efficacy and engagement in CS studies. This study's anticipated contributions are manifold: providing empirical evidence on the effectiveness of chatbots in CS education, comparing learner outcomes between those who engage with chatbots and those who do not, and offering strategic recommendations for AI integration into teaching methods. The insights derived from this research could guide policy-makers and curriculum designers in adapting new methods in the era of Chatbots.

Immersive Virtual Reality in Education: Training, Teaching, Learning and Assessment processes in Schools in Israel

Esti Schwartz, PHD Student, Department of Education and Psychology: Technologies and Learning Systems program, The Open University of Israel.

Immersive Virtual Reality has the potential to revolutionize education by providing student-centered, engaging learning experiences. VR takes various forms in schools, such as desktop virtual reality (DVR), immersive classrooms (IR), and head-mounted display virtual reality (HMD-VR), each with different levels of immersion. While educational use of VR enhances engagement and knowledge retention, it also poses challenges such as cognitive overload and privacy concerns. This research innovatively explores established educational frameworks in VR learning settings, specifically the e-CSAMR framework, combining the SAMR model with an e-collaboration classification, and a Teacher Prototypes typology. The study aims to explore professional development for VR teaching, changes in teaching and learning processes. Using a mixed-methods approach with multiple case studies, the research involves 36 teachers, 36 students, 12 ICT training instructors, and 12 ICT school coordinators. The study will observe actual learning in all three VR modalities- DVR, IR and HMD-VR and interview the participants. Ultimately, this research enhances teaching, learning, assessment and teacher training, in VR-based education, contributing to the e-CSAMR and Teacher Prototypes frameworks.

The Impact of Avatar Similarity to a Human, Based ChatGPT, on the Effectiveness of Training to Improve Soft Skills

Nirit Gavish & Itzik Ben-Shlush, Braude College of Engineering, Carmiel

The rise of large language models (LLMs) sparked the question of how to communicate optimally with them. Since large language models learn through self-supervision and are based on billions of parameters, they possess communication skills and understand interpersonal communication. However, while they are capable of generating responses in communication with users, there is still a challenge in predicting their responses accurately, as these models, though highly advanced, are not always able to handle real-life communication scenarios as efficiently as humans. The challenge lies in how to effectively use the models for communication, especially when interacting with them through interfaces like text-based communication. The research explores this challenge, focusing on soft skills improvement by using an avatar-based task in virtual or augmented reality environments. In the proposed study, the task involves role-playing a job interview with an avatar that is based on a soft skills training model. The participant trains with ChatGPT through this avatar, which plays the role of an interviewer, asking questions related to the job. The avatar is designed to provide feedback on the trainee's performance. A key question in this research is how similar the avatar should be to a human. On one hand, the more the avatar resembles a human, the more realistic and familiar the interaction will feel, increasing the likelihood of the trainee treating the interaction seriously. On the other hand, if the avatar resembles a human too much, the trainee might mistakenly apply interpersonal communication knowledge to the avatar interaction, assuming it follows the same patterns as human interaction. The research will use the EON-XR commercial system to facilitate this training, measuring trainee performance during the job interview through the system, and examining subjective feedback on how the trainee perceives their improvement in soft skills.

Outstanding Dissertation and Student Paper Awards

Outstanding Dissertation - Chais 2026

Improving Selection for Surgical Training: Using Virtual Reality and Gamification for Assessment of Technical Skills, Cognitive Abilities, and Personality Characteristics
Dr. Noa Gazit-Dadush - Hebrew University of Jerusalem

The selection of candidates for surgical training is a crucial step in identifying the most suitable candidates for a surgical career. However, in most surgical programs worldwide the selection process is based on ineffective methods such as CVs, academic achievement, letters of recommendation, and unstructured interviews, which show zero to low correlation with later performance during residency. Traditional personnel-selection tools (e.g., dexterity tests, visuospatial ability tests, and personality questionnaires) have also been examined but have not been found suitable for selecting candidates for surgical training. Therefore, the aim of this research was to develop improved selection tools and to validate their use in the selection of candidates for surgical training.

The research included three phases. In Phase 1, a job analysis was conducted to identify the competencies required of surgeons in the 21st century. Based on interviews with expert surgeons (N = 104), 24 competencies were identified: five technical skills, six cognitive abilities, and 13 personality characteristics. This list was later validated using a questionnaire completed by a large sample of surgeons and residents (N = 1,102). In Phase 2, two virtual reality (VR) game-based assessment tests were developed: a technical aptitude test using a VR laparoscopic simulator and a computer game-based assessment of cognitive abilities and personality characteristics. Finally, in Phase 3, validity evidence for the tests was examined using data collected from interns, residents, and expert surgeons. The findings provided significant evidence for the validity, fairness, and feasibility of the tests and support their use in the selection of candidates for surgical training.

In summary, the dissertation presents the systematic development and evaluation of two VR game-based assessments with the potential to improve the selection process for surgical training. Improving the selection process may contribute to improving the quality of the surgical workforce and patient care.

Student Paper Award

Between Awareness and Implementation: Redefining Lecturer Roles in the GenAI Era

Efrat Fass & Prof. Tami Seifert
Kibbutzim College of Education, Technology and the Arts

The emergence of Generative Artificial Intelligence (GenAI) tools presents academia with a fundamental question regarding the evolving role of faculty members in this new technological landscape. This paper examines how faculty in higher education interpret the changes in their professional role in the GenAI era and explores the ways in which these tools influence teaching practices and assessment methods. The study employed a mixed-methods design that included an online survey completed by 205 faculty members from universities, academic colleges, and teacher education colleges in Israel, alongside 16 semi-structured interviews that provided deeper insight into lecturers' experiences and perspectives. The integration of quantitative and qualitative data revealed a paradigmatic shift in faculty role perception, within which four adaptation types were identified. Faculty members who actively engage with GenAI tend to adopt a broader pedagogical role that emphasizes facilitation, learning design, and critical engagement with content. In the teaching domain, three central patterns emerged: technical use for preparing course materials, pedagogical use that supports active and dialogic learning, and meta-cognitive practices that invite students to reflect on their learning processes. Considerable variation was found among faculty in both the extent and the nature of GenAI integration. Assessment emerged as the most challenging domain. Only part of the faculty reported meaningful changes to their assessment practices, reflecting concerns around authenticity, academic integrity, and the relevance of traditional assignments in an era of automated text generation. The findings highlight the gap between awareness of the need for change and its implementation in practice. Path analysis reveals that changes in teaching and assessment practices mediate the relationship between GenAI usage and faculty role perception. This paper offers a framework for understanding the transformation across these three domains and underscores the need to continue developing teaching and assessment approaches that align with the realities of the GenAI era.

Click here for the full paper (in Hebrew)