Ido Roll
Biographic Data
| ID | 4609348 |
|---|---|
| NAME | Ido Roll |
| GIVEN NAMES | Ido |
| FAMILY NAME | Roll |
| SIGNATURE | ROLL I |
| AFFILIATIONS | Technion – Israel Institute of Technology |
| ORCID | 0000-0001-7295-9059 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 3 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Measuring different types and domains of AI knowledge: Developing and validating a performance-based scale
As artificial intelligence (AI) and generative AI (GenAI) technologies become increasingly integrated into everyday life, the need for validated tools that measure people’s knowledge about AI grows. Here, we present the development and validation of a theoretically driven, performance-based scale for assessing AI and GenAI knowledge. The scale is grounded in a two-axial framework. One axis captures three knowledge types: content knowledge (what A…
Minding the gender gap in advanced STEM courses: Effects of student preparedness and activity level
The gender achievement gap in higher STEM education is well documented as STEM course grades often show a bias favoring men, even when controlling for overall student achievements. The current work, which was preregistered prior to data collection, replicates and extends prior work to evaluate several possible contributors to the gender gap in advanced STEM courses. The contributing factors include students’ STEM-preparedness, learning assessment…
Learning about multivariable causality with interactive simulations: Exploration Before Instruction May Hurt Immediate Gains but Benefits Transfer
Studying complex interactions between variables to comprehend phenomena can be challenging for students of all ages. Simulations are often used to facilitate exploratory learning of complex phenomena, but students still face difficulties in comprehending interactions between factors. This study examined the comparative effectiveness of the Problem-Solving before Instruction (PS-I) approach versus the Instruction before Problem Solving approach (I…
Investigating the order of example-problem sequences when learning experimental design and graphing competencies
This study investigates the order of examples and problems in example-based learning, a pedagogical approach that provides learners with step-by-step solutions to new problems early in the learning process. Worked examples have been found to be very effective when combined with open problems, mostly in well-structured topics. Despite extensive research in this area, questions persist about the optimal sequencing of examples and problems. The stud…
Supporting students’ self-regulated learning in online learning using artificial intelligence applications
Self-regulated learning (SRL) is crucial for helping students attain high academic performance and achieve their learning objectives in the online learning context. However, learners often face challenges in properly applying SRL in online learning environments. Recent developments in artificial intelligence (AI) applications have shown promise in supporting learners’ self-regulation in online learning by measuring and augmenting SRL, but researc…
Interface and interaction design for an online, asynchronous peer instruction tool
This article describes the design and evaluation of an online, asynchronous tool that mirrors the beneficial peer instruction process currently conducted in face-to-face classrooms. In the online Peer Instruction tool, students respond to a multiple-choice question with an answer and explanation. They are then exposed to peer responses to the same question. Finally, they may optionally submit a revised response, formed after exposure to these pee…
Rethinking (Dis)engagement in human-computer interaction
User engagement has become a much-cited construct in human-computer interaction (HCI) design and evaluation research and practice. Constructed as a positive and desirable outcome of users' interactions, more frequent and longer interactions are considered evidence of engagement. Disengagement, when discussed, is considered a best avoided outcome of technology use or a solution to problematic technology use. In the case of the former, disengagemen…
The impact of artificial intelligence on learner–instructor interaction in online learning
Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors’ routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner–instructo…
Active learning with online video: The impact of learning context on engagement
Towards a Theory of When and How Problem Solving Followed by Instruction Supports Learning
Evolution and Revolution in Artificial Intelligence in Education
Learning about multivariable causality with interactive simulations: Exploration Before Instruction May Hurt Immediate Gains but Benefits Transfer
Studying complex interactions between variables to comprehend phenomena can be challenging for students of all ages. Simulations are often used to facilitate exploratory learning of complex phenomena, but students still face difficulties in comprehending interactions between factors. This study examined the comparative effectiveness of the Problem-Solving before Instruction (PS-I) approach versus the Instruction before Problem Solving approach (I…
Investigating the order of example-problem sequences when learning experimental design and graphing competencies
This study investigates the order of examples and problems in example-based learning, a pedagogical approach that provides learners with step-by-step solutions to new problems early in the learning process. Worked examples have been found to be very effective when combined with open problems, mostly in well-structured topics. Despite extensive research in this area, questions persist about the optimal sequencing of examples and problems. The stud…
Evolution and Revolution in Artificial Intelligence in Education
Towards a Theory of When and How Problem Solving Followed by Instruction Supports Learning
The impact of artificial intelligence on learner–instructor interaction in online learning
Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors’ routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner–instructo…
Active learning with online video: The impact of learning context on engagement
Rethinking (Dis)engagement in human-computer interaction
User engagement has become a much-cited construct in human-computer interaction (HCI) design and evaluation research and practice. Constructed as a positive and desirable outcome of users' interactions, more frequent and longer interactions are considered evidence of engagement. Disengagement, when discussed, is considered a best avoided outcome of technology use or a solution to problematic technology use. In the case of the former, disengagemen…
Supporting students’ self-regulated learning in online learning using artificial intelligence applications
Self-regulated learning (SRL) is crucial for helping students attain high academic performance and achieve their learning objectives in the online learning context. However, learners often face challenges in properly applying SRL in online learning environments. Recent developments in artificial intelligence (AI) applications have shown promise in supporting learners’ self-regulation in online learning by measuring and augmenting SRL, but researc…
Interface and interaction design for an online, asynchronous peer instruction tool
This article describes the design and evaluation of an online, asynchronous tool that mirrors the beneficial peer instruction process currently conducted in face-to-face classrooms. In the online Peer Instruction tool, students respond to a multiple-choice question with an answer and explanation. They are then exposed to peer responses to the same question. Finally, they may optionally submit a revised response, formed after exposure to these pee…
Minding the gender gap in advanced STEM courses: Effects of student preparedness and activity level
The gender achievement gap in higher STEM education is well documented as STEM course grades often show a bias favoring men, even when controlling for overall student achievements. The current work, which was preregistered prior to data collection, replicates and extends prior work to evaluate several possible contributors to the gender gap in advanced STEM courses. The contributing factors include students’ STEM-preparedness, learning assessment…
Learning about multivariable causality with interactive simulations: Exploration Before Instruction May Hurt Immediate Gains but Benefits Transfer
Studying complex interactions between variables to comprehend phenomena can be challenging for students of all ages. Simulations are often used to facilitate exploratory learning of complex phenomena, but students still face difficulties in comprehending interactions between factors. This study examined the comparative effectiveness of the Problem-Solving before Instruction (PS-I) approach versus the Instruction before Problem Solving approach (I…
Investigating the order of example-problem sequences when learning experimental design and graphing competencies
This study investigates the order of examples and problems in example-based learning, a pedagogical approach that provides learners with step-by-step solutions to new problems early in the learning process. Worked examples have been found to be very effective when combined with open problems, mostly in well-structured topics. Despite extensive research in this area, questions persist about the optimal sequencing of examples and problems. The stud…
Measuring different types and domains of AI knowledge: Developing and validating a performance-based scale
As artificial intelligence (AI) and generative AI (GenAI) technologies become increasingly integrated into everyday life, the need for validated tools that measure people’s knowledge about AI grows. Here, we present the development and validation of a theoretically driven, performance-based scale for assessing AI and GenAI knowledge. The scale is grounded in a two-axial framework. One axis captures three knowledge types: content knowledge (what A…
Computer Science (8 works) · Psychology (8 works) · Innovative Teaching and Learning Methods (6 works) · Mathematics education (6 works) · Online and Blended Learning (5 works) · Online Learning and Analytics (4 works) · Artificial Intelligence (3 works) · Cognition (3 works) · Educational psychology (3 works) · Intelligent Tutoring Systems and Adaptive Learning (3 works)