@article{price_liu_catete_barnes_2017, place={New York, NY, USA}, title={Factors Influencing Students' Help-Seeking Behavior while Programming with Human and Computer Tutors}, url={https://doi.org/10.1145/3105726.3106179}, DOI={10.1145/3105726.3106179}, abstractNote={When novice students encounter difficulty when learning to program, some can seek help from instructors or teaching assistants. This one-on-one tutoring is highly effective at fostering learning, but busy instructors and large class sizes can make expert help a scarce resource. Increasingly, programming environments attempt to imitate this human support by providing students with hints and feedback. In order to design effective, computer-based help, it is important to understand how and why students seek and avoid help when programming, and how this process differs when the help is provided by a human or a computer. We explore these questions through a qualitative analysis of 15 students' interviews, in which they reflect on solving two programming problems with human and computer help. We discuss implications for help design and present hypotheses on students' help-seeking behavior.}, journal={PROCEEDINGS OF THE 2017 ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH (ICER 17)}, publisher={Association for Computing Machinery}, author={Price, Thomas W. and Liu, Zhongxiu and Catete, Veronica and Barnes, Tiffany}, year={2017}, pages={127–135} }
 @article{liu_zhi_hicks_barnes_2017, title={Understanding problem solving behavior of 6-8 graders in a debugging game}, volume={27}, ISSN={["1744-5175"]}, DOI={10.1080/08993408.2017.1308651}, abstractNote={Abstract Debugging is an over-looked component in K-12 computational thinking education. Few K-12 programming environments are designed to teach debugging, and most debugging research were conducted on college-aged students. In this paper, we presented debugging exercises to 6th–8th grade students and analyzed their problem solving behaviors in a programming game – BOTS. Apart from the perspective of prior literature, we identified student behaviors in relation to problem solving stages, and correlated these behaviors with student prior programming experience and performance. We found that in our programming game, debugging required deeper understanding than writing new codes. We also found that problem solving behaviors were significantly correlated with students’ self-explanation quality, number of code edits, and prior programming experience. This study increased our understanding of younger students’ problem solving behavior, and provided actionable suggestions to the future design of debugging exercises in BOTS and similar environments.}, number={1}, journal={COMPUTER SCIENCE EDUCATION}, author={Liu, Zhongxiu and Zhi, Rui and Hicks, Andrew and Barnes, Tiffany}, year={2017}, pages={1–29} }
 @article{liu_mostafavi_barnes_2016, title={Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor}, volume={9684}, ISBN={["978-3-319-39582-1"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-319-39583-8_40}, abstractNote={Previous research has shown that worked examples can increase learning efficiency during computer-aided instruction, especially when alternatively offered with problem solving opportunities. In this study, we investigate whether these results are consistent in a complex, open-ended problem solving domain, where students are presented with randomly ordered sets of worked examples and required problem solving. Our results show that worked examples benefits students early in tutoring sessions, but are comparable to hint-based systems for scaffolding domain concepts. Later in tutoring sessions, worked examples are less beneficial, and can decrease performance for lower-proficiency students.}, journal={INTELLIGENT TUTORING SYSTEMS, ITS 2016}, author={Liu, Zhongxiu and Mostafavi, Behrooz and Barnes, Tiffany}, year={2016}, pages={347–353} }
 @article{liu_barnes_2015, title={Building Compiler-Student Friendship}, volume={9112}, ISBN={["978-3-319-19772-2"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-319-19773-9_129}, abstractNote={Previous studies have shown that compilers positively influence students when they are designed to build connections with students. In this paper, I propose to study the use of a friendly compiler for young novice programmers. This study involves designing compiler messages that incorporate a friendship model. The goal is to make students view compiler as a friend, instead of as an error-picking authority. I hypothesize that a good compiler-student relationship will change students’ attitude, self-efficacy and motivation towards programming, as well as change students compilation behaviors.}, journal={ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2015}, author={Liu, Zhongxiu and Barnes, Tiffany}, year={2015}, pages={844–847} }