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Javeed Kittur

Biographic Data

ID9259752
NAMEJaveed Kittur
GIVEN NAMESJaveed
FAMILY NAMEKittur
SIGNATUREKITTUR J
AFFILIATIONSPathways Behavioral Services
ORCID0000-0001-6132-7304
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Shaping tomorrow’s classrooms: What engineering doctoral students expect as future educators

    Open Access•Omar J Garcia, Javeed Kittur•ARTICLE•Frontiers in Education•2026

    Introduction Engineering doctoral students who pursue careers in academia will be required to teach courses; however, their PhD programs typically result in much less teaching experience compared to research experience. Most teaching experience occurs through graduate teaching assistantships, which may include training but involve a wide variety of roles. While some doctoral students seek additional instructional positions during their PhD progra…

  • Strategic innovations and future directions in deep learning for engineering applications: A systematic literature review

    Open Access•Arianna G Tobias, Javeed Kittur•ARTICLE•Frontiers in Education•2025

    Background Deep learning (DL), a subset of machine learning and artificial intelligence (AI), is transforming engineering by addressing complex problems with innovative solutions. Despite its growing influence, a comprehensive review of current trends, applications, and research gaps in engineering disciplines is essential to understand its full potential, limitations, and potential educational implications. Purpose This study systematically expl…

  • Understanding the Current Mentorship Capabilities of Teaching Assistants for Engineering Courses

    Open Access•Nathan G Ewert, Javeed Kittur•ARTICLE•IEEE Transactions on Education•2025

    Contribution: This article describes and interprets the quantitative results from a survey meant to evaluate the mentorship capabilities of engineering teaassistants. Background: TA are a common facet at several higher learning institutions. In this position, they perform multiple duties to improve their students’ learning experiences, refining their own teaching abilities in the process. Given both their prevalence and impact, various researcher…

  • Measuring the Programming Self-Efficacy of Electrical and Electronics Engineering Students

    Open Access•Javeed Kittur•ARTICLE•IEEE Transactions on Education•2020

    Contribution: This article has shown that self-efficacy in performing complex computer programming tasks and the self-regulation of electrical and electronics engineering undergraduate students varies with respect to the class standing and prior experience in computer programming. Background: Computer programming is an essential skill that all engineers must possess, as most industries require engineers to own this skill. Prior studies discuss pr…

No prominent works on this page.

  • Measuring the Programming Self-Efficacy of Electrical and Electronics Engineering Students

    Open Access•Javeed Kittur•ARTICLE•IEEE Transactions on Education•2020

    Contribution: This article has shown that self-efficacy in performing complex computer programming tasks and the self-regulation of electrical and electronics engineering undergraduate students varies with respect to the class standing and prior experience in computer programming. Background: Computer programming is an essential skill that all engineers must possess, as most industries require engineers to own this skill. Prior studies discuss pr…

  • Strategic innovations and future directions in deep learning for engineering applications: A systematic literature review

    Open Access•Arianna G Tobias, Javeed Kittur•ARTICLE•Frontiers in Education•2025

    Background Deep learning (DL), a subset of machine learning and artificial intelligence (AI), is transforming engineering by addressing complex problems with innovative solutions. Despite its growing influence, a comprehensive review of current trends, applications, and research gaps in engineering disciplines is essential to understand its full potential, limitations, and potential educational implications. Purpose This study systematically expl…

  • Understanding the Current Mentorship Capabilities of Teaching Assistants for Engineering Courses

    Open Access•Nathan G Ewert, Javeed Kittur•ARTICLE•IEEE Transactions on Education•2025

    Contribution: This article describes and interprets the quantitative results from a survey meant to evaluate the mentorship capabilities of engineering teaassistants. Background: TA are a common facet at several higher learning institutions. In this position, they perform multiple duties to improve their students’ learning experiences, refining their own teaching abilities in the process. Given both their prevalence and impact, various researcher…

  • Shaping tomorrow’s classrooms: What engineering doctoral students expect as future educators

    Open Access•Omar J Garcia, Javeed Kittur•ARTICLE•Frontiers in Education•2026

    Introduction Engineering doctoral students who pursue careers in academia will be required to teach courses; however, their PhD programs typically result in much less teaching experience compared to research experience. Most teaching experience occurs through graduate teaching assistantships, which may include training but involve a wide variety of roles. While some doctoral students seek additional instructional positions during their PhD progra…

Engineering education (3 works) · Computer Science (2 works) · Engineering (2 works) · Engineering management (2 works) · Exploratory factor analysis (2 works) · Regression analysis (2 works) · Anomaly Detection Techniques and Applications (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Class (philosophy) (1 works)

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