A5002187823- Teaching and Learning Programming
- Online Learning and Analytics
- Experimental Learning in Engineering
- Innovative Teaching Methods
- Innovative Teaching and Learning Methods
- Online and Blended Learning
- Educational Games and Gamification
- Parallel Computing and Optimization Techniques
- Advanced Data Storage Technologies
- Genetics, Bioinformatics, and Biomedical Research
- Information Systems Education and Curriculum Development
- Cloud Computing and Resource Management
- Student Assessment and Feedback
- Distributed and Parallel Computing Systems
- Cinema and Media Studies
- Interconnection Networks and Systems
- Statistics Education and Methodologies
- Science Education and Pedagogy
- Gender and Technology in Education
- Intelligent Tutoring Systems and Adaptive Learning
- Education, Achievement, and Giftedness
- Mathematics, Computing, and Information Processing
- Software Engineering Research
- Advanced Malware Detection Techniques
- Career Development and Diversity
University of California, San Diego
2016-2025
Carnegie Mellon University
2024
University of Auckland
2024
Temple University
2024
University of California System
2016
EP Analytics (United States)
2015
Skidmore College
2012-2014
Cleveland Research (United States)
1931
Federal Reserve Board of Governors
1930
Eastman Chemical Company (United States)
1930
Providing timely and personalized feedback to large numbers of students is a long-standing challenge in programming courses.Relying on human teaching assistants (TAs) has been extensively studied, revealing number potential shortcomings.These include inequitable access for with low confidence when needing support, as well situations where TAs provide direct solutions without helping develop their own problemsolving skills.With the advent powerful language models (LLMs), digital configured...
Peer Instruction (PI) is an instructional approach that engages students in constructing their own understanding of concepts. Students individually respond to a question, discuss with peers, and the same question again. In general, peer discussion portion PI leads increase number answering correctly. But are these really learning, or they just "copying" right answer from someone group? article journal Science, Smith et al. affirm genetics learn discussion: having discussed first better able...
How pair programming, peer instruction, and media computation have improved computer science education.
Peer Instruction (PI) is a teaching method that supports student-centric classrooms, where students construct their own understanding through structured approach featuring questions with peer discussions. PI has been shown to increase learning in STEM disciplines such as physics and biology. In this report we look at another indicator of student success the rate which pass course or, conversely, they fail. Evaluating 10 years instruction 4 different courses spanning 16 instances, find...
Beginning in 2008, we introduced a new CS1 incorporating trio of best practices intended to improve the quality course, appeal broader student body, and, hopefully, retention major. This included Media Computation, Pair Programming, and Peer Instruction. After 3 1/2 years (8 classes, different instructors, 1011 students passing course) find that 89% majors who pass course are still studying computing one year later. is an improvement 18% over our average 71% for previous version (measured...
Concept Inventories (CIs) are assessments designed to measure student learning of core concepts. CIs have become well known for their major impact on pedagogical techniques in other sciences, especially physics. Presently, there no widely used, validated computer science. However, considerable groundwork has been performed the form identifying concepts, analyzing misconceptions, and developing CI assessment questions. Although much work focused CS1 a developed digital logic, some preliminary...
Recent research suggests that the first weeks of a CS1 course have strong influence on end-of-course student performance. The present work aims to refine understanding this phenomenon by using in-class clicker questions as source Clicker generate per-lecture and per-question data with which assess understanding. This demonstrates question performance early in term predicts outcomes at end term. predictive nature these applies code-writing questions, multiple choice final exam whole. most are...
As enrollments and class sizes in postsecondary institutions have increased, instructors sought automated lightweight means to identify students who are at risk of performing poorly a course. This identification must be performed early enough the term allow assist those before they fall irreparably behind. study describes modeling methodology that predicts student final exam scores third week by using clicker data is automatically collected for when employ Peer Instruction pedagogy. The...
Students' sense of belonging has been found to be connected student retention in higher education. In computing education, prior studies suggest that a hostile culture and feeling non-belonging can lead women, Black, Latinx, Native American, Pacific Islander students drop out the field at disproportionately high rate. Yet, we know relatively little about how students' presents evolves (if all) through their college courses, particularly courses beyond introductory level, is known impacts...
Peer Instruction (PI) is an active learning pedagogical technique. PI lectures present students with a series of multiple-choice questions, which they respond to both individually and in groups. has been widely successful the physical sciences and, recently, successfully adopted by computer science instructors lower-division, introductory courses. In this work, we challenge readers consider for their upper-division courses as well. We curriculum two courses: Computer Architecture Theory...
Peer Instruction (PI) has a significant following in physics, biology, and chemistry education. Although many CS educators are aware of PI as pedagogy, the adoption rate is low. This paper reports on four instructors with varying motivations course contexts value they found adopting PI. there documented benefits for students (e.g. increased learning), here we describe experience instructor by looking detail at one particular question posed class. Through discussion instructors' experiences...
Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants classroom. Over past five years, there have been number research articles regarding value PI computer science. The present work adds this body knowledge by examining outcomes seven introductory programming instructors: three novices and four with range experience. Through common measurements student perceptions, we provide evidence that computing instructors...
Being able to identify low-performing students early in the term may help instructors intervene or differently allocate course resources. Prior work CS1 has demonstrated that clicker correctness Peer Instruction courses correlates with exam outcomes and, separately, machine learning models can be built based on early-term programming assessments. This aims combine best elements of each these approaches. We offer a methodology for creating models, in-class questions, predict cross-term...
It is generally assumed that early success in CS1 crucial for on the exam and course as a whole. Particularities of students, densely-connected content, recurring core topics each suggest it difficult to rebound from misunderstandings. In this paper, we use Peer Instruction (PI) data, addition explore relationships between in-class assessments performance at end term exam. We find very quickly strongly predicts final subsequent weeks provide no major increase predictive power. contrast,...
A Concept Inventory (CI) is a validated assessment to measure student conceptual understanding of particular topic. This work presents CI for Basic Data Structures (BDSI) and the process by which was designed validated. We discuss: 1) collection faculty opinions from diverse institutions on what belongs instrument, 2) series interviews with students identify their conceptions misconceptions content, 3) an iterative design developing draft questions, conducting ensure questions instrument are...
The Impostor Phenomenon (IP) is often discussed as a problem in the field of computer science, but there has yet to be an empirical study establish its prevalence among CS students. One survey by Blind app found that high number software engineers at some largest technology companies self-reported feelings Syndrome; however, self-reporting Syndrome not standard diagnostic for identifying whether individual exhibits Phenomenon. In this work, established Clance IP Scale used identify graduate...
Computer science students struggle in early computing courses as evinced by high failure rates and poor retention. As such, studies have attempted to characterize the root of student struggles from many perspectives, including cognitive, meta-cognitive, social emotional. Typically, limited their inquiry a specific perspective or single course. This paper reports results broad experience survey conducted across several computer courses. Through periodic survey, rated various socio-emotional,...
Previous reports of a media computation approach to teaching programming have either focused on pre-CS1 courses or for non-majors. We report the adoption context in majors' CS1 course at large, selective R1 institution U.S. The main goal was increase retention majors, but do so by replacing traditional directly (fully preparing students subsequent course). In this paper we provide an experience instructors interested approach. compare with terms desired student competencies (analyzed via...
Peer Instruction (PI) has been shown to be successful at improving pass-rates and retention of majors in large classes research-intensive institutions. At these institutions, students have learn from peer discussion PI both faculty reported that they value their classrooms. However, little is known about the effectiveness small classrooms teaching-focused liberal arts colleges. This study evaluates results seven lower-division four upper-division taught three different institutions using PI....
Achievement goals are cognitively-represented end states that individuals strive to reach in competence situations. Well-studied by educational psychologists, achievement robust predictors of grades, interest, and motivation students. In this paper, we apply goal theory measure CS1 students' consequent interest CS final exam grade. We find students aiming for topic mastery become interested and, contrary theoretical expectations, perform well on the exam. A more complex pattern results...