Maya Israel

Associate Professor University of Florida

  • Gainesville FL

Maya Israel researches how to support academically diverse learners’ meaningful engagement in computer science education.

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University of Florida

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Biography

Maya Israel is an associate professor of educational technology and computer science (CS) education. She is the director of the Kenneth C. Griffin CS Education for All Initiative and the Creative Technology Research Lab. Her research research focuses on K-12 computer science teacher education and strategies for supporting students with disabilities and other struggling learners' meaningful engagement in science, technology, engineering, and mathematics (STEM) with emphases on computational thinking, computer science education, and Universal Design for Learning (UDL).

Areas of Expertise

Technology Integration
Computer Science Education
Special Education
Universal Design for Learning

Media Appearances

At UF, we are working together to provide Florida teachers and students with computer science skills

Tampa Bay Times  print

2021-11-26

In a world driven by technological innovation, we should be teaching all young learners computer skills from the earliest grades. In fact, Florida HB 495, enacted in 2018, requires all middle and high schools to provide computer science courses. It would seem, then, that all Florida students would have the same opportunity to learn computer science. But many school districts struggle to offer computer science education, especially rural districts and those serving less-affluent students.

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Social

Articles

Uncovering students’ problem-solving processes in game-based learning environments

Computers & Education

Tongxi Liu and Maya Israel

2022-06-01

(Forthcoming) As one of the most desired skills for contemporary education and career, problem-solving is fundamental and critical in game-based learning research. However, students' implicit and self-controlled learning processes in games make it difficult to understand their problem-solving behaviors. Observational and qualitative methods, such as interviews and exams, fail to capture students' in-process difficulties. By integrating data mining techniques, this study explored students' problem-solving processes in a puzzle-based game.

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Elementary Computational Thinking Instruction and Assessment: A Learning Trajectory Perspective

Association for Computing Machinery

Feiya Luo, Maya Israel and Brian Gane

2022-02-09

There is little empirical research related to how elementary students develop computational thinking (CT) and how they apply CT in problem-solving. To address this gap in knowledge, this study made use of learning trajectories (LTs; hypothesized learning goals, progressions, and activities) in CT concept areas such as sequence, repetition, conditionals, and decomposition to better understand students’ CT. This study implemented eight math-CT integrated lessons aligned to U.S. national mathematics education standards and the LTs with third- and fourth-grade students.

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A descriptive analysis of academic engagement and collaboration of students with autism during elementary computer science

Computer Science Education

Maya Israel, et al.

2020-10-23

Elementary computer science (CS) can be engaging and challenging for some students with disabilities who struggle with complex problem solving.

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Spotlight

4 min

AI in the classroom: What parents need to know

As students return to classrooms, Maya Israel, professor of educational technology and computer science education at the University of Florida, shares insights on best practices for AI use for students in K-12. She also serves as the director of CSEveryone Center for Computer Science Education at UF, a program created to boost teachers’ capabilities around computer science and AI in education. Israel also leads the Florida K-12 Education Task Force, a group committed to empowering educators, students, families and administrators by harnessing the transformative potential of AI in K-12 classrooms, prioritizing safety, privacy, access and fairness. How are K–12 students using AI in classrooms? There is a wide range of approaches that students are using AI in classrooms. It depends on several factors including district policies, student age and the teacher’s instructional goals. Some districts restrict AI to only teacher use, such as creating custom reading passages for younger students. Others allow older students to use tools to check grammar, create visuals or run science simulations. Even then, skilled teachers frame AI as one tool, not a replacement for student thinking and effort. What are examples of age-appropriate tools that enhance learning? AI tools can be used to either enhance or erode learner agency and critical thinking. It is up to the educators to consider how these tools can be used appropriately. It is critical to use AI tools in a manner that supports learning, creativity and problem solving rather than bypass critical thinking. For example, Canva lets students create infographics, posters and videos to show understanding. Google’s Teachable Machine helps students learn AI concepts by training their own image-recognition models. These types of AI-augmented tools work best when they are embedded into activities such as project-based learning, where AI supports learning and critical thinking. How do teachers ensure AI supports core skills? While AI can be incredibly helpful in supporting learning, it should not be a shortcut that allows students to bypass learning. Teachers should design learning opportunities that integrate AI in a manner that encourages critical thinking. For example, if students are using AI to support their mathematical understanding, teachers should ask them to explain their reasoning, engage in discussions and attempt to solve problems in different ways. Teachers can ask students questions like, “Does that answer make sense based on what you know?” or “Why do you think [said AI tool] made that suggestion?” This type of reflection reinforces the message that learning does not happen through getting fast answers. Learning happens through exploration, productive struggle and collaboration. Many parents worry that using AI might make students too dependent on technology. How do educators address that concern? This is a very valid concern. Over-reliance on AI can erode independence and critical thinking, that’s why teachers should be intentional in how they use AI for teaching and learning. Educators can address this concern by communicating with parents their policies and approaches to using AI with students. This approach can include providing clear expectations of when AI is used, designing assignments that require critical thinking, personal reflection and reasoning and teaching students the metacognitive skills to self-assess how and when to use AI so that it is used to support learning rather than as a crutch. How do schools ensure that students still develop original thinking and creativity when using AI for assignments or projects? In the age of AI, there is the need to be even more intentional designing learning experiences where students engage in creative and critical thinking. One of the best practices that have shown to support this is the use of project-based learning, where students must create, iterate and evaluate ideas based on feedback from their peers and teachers. AI can help students gather ideas or organize research, but the students must ask the questions, synthesize information and produce original ideas. Assessment and rubrics should emphasize skills such as reasoning, process and creativity rather than just focusing on the final product. That way, although AI can play a role in instruction, the goal is to design instructional activities that move beyond what the AI can do. How do educators help students understand when it’s appropriate to use AI in their schoolwork? In the age of AI, educators should help students develop the skills to be original thinkers who can use AI thoughtfully and responsibly. Educators can help students understand when to use AI in their school work by directly embedding AI literacy into their instruction. AI literacy includes having discussions about the capabilities and limitations of AI, ethical considerations and the importance of students’ agency and original thoughts. Additionally, clear guidelines and policies help students navigate some of the gray areas of AI usage. What guidance should parents give at home? There are several key messages that parents should give their children about the use of AI. The most important message is that even though AI is powerful, it does not replace their judgement, creativity or empathy. Even though AI can provide fast answers, it is important for students to learn the skills themselves. Another key message is to know the rules about AI in the classroom. Parents should speak with their students about the mental health implications of over-reliance on AI. When students turn to AI-augmented tools for every answer or idea, they can gradually lose confidence in their own problem-solving abilities. Instead, students should learn how to use AI in ways that strengthen their skills and build independence.

Maya Israel