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1. Effect of Immediate Feedback on Math Achievement at the High School Level

   https://doi.org/10.1007/978-3-030-52240-7_48  

   Razzaq, Reenah; Ostrow, Korinn S.; Heffernan, Neil T. (January 2020, Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science)

   We examine the use of computer-based learning in the classroom and the effect of immediate feedback on student performance. Since it is well known in educational research that it is possible to observe a “Matthew Effect” in which the rich get richer, we wanted to see if feedback was useful for low prior knowledge students, as defined by students whose pretest score was at or below the median. In this counterbalanced randomized controlled trial, 243 tenth and eleventh grade mathematics students were exposed to one of two conditions, as we measured their learning from: 1) immediate feedback (where the computer told them correctness and they could also ask for hints) or 2) practice only (where they received feedback only after taking a posttest). Results suggest that immediate feedback from computer-based learning tasks benefit both high and low prior knowledge students, with low prior knowledge students exhibiting greater gains. The implications of these findings support further investigation into the use of computer-based learning tasks that provide immediate feedback. 

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2. Work in Progress: The Electric Circuit Concepts Diagnostic (ECCD)

   Hunsu, N. (January 2022, Annual Proceeding of the American Society for Engineering Education)

   Students come to learning in engineering classrooms with misconceptions about the concepts covered in engineering course contents. However, instructional efforts often do not effectively address misconceptions in students’ prior knowledge. Concept inventories (CIs) are often relied upon to identify misconceptions in students’ prior knowledge. However, many instructors never benefit much from using CIs because they lack either the know-how, time commitment, or statistical skills required to use them efficiently and effectively. Furthermore, there sometimes are ambiguities about how to interpret students’ CI scores. The Electric Circuit Concepts Diagnostic (ECCD) project team will address these limitations of CIs by creating a web-based electric circuit concept inventory that: (i.) provides an immediate and multipurpose feedback system for reporting about students’ circuits and electricity prior knowledge; (ii.) differentiates, with a high probability, between a lack of prior knowledge and misconceptions; and (iii.) uses a scheme of multidimensional knowledge profiles to report on students’ prior knowledge and misconceptions. The project will integrate the affordances of cognitive diagnostic modeling (CDM), multitier testing frameworks, and computer-assisted testing to realize these project objectives. This work-in-progress report introduces the objectives of ECCD inventory to the ECE research and teaching community. 

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3. The Effectiveness of Full and Focused Structural Feedback on Students’ Knowledge Structure and Learning

   https://doi.org/10.1007/s10758-025-09892-0  

   Wang, Yu; Solnosky, Ryan; Clariana, Roy_B (August 2025, Technology, Knowledge and Learning)

   Abstract Most STEM classrooms overlook the intrinsic conceptual structure of domain content, strategies for improving students’ conceptual structure have promise for improving STEM learning outcomes. This experimental investigation continues the development of the web-based toolGraphical Interface of Knowledge Structure (GIKS)that provides immediate formative feedback as a network of concepts in the student’s essays alongside an expert referent network for comparison and reflection. What should this feedback network look like, especially, should it be more inclusive or small and focused? And is preexisting domain knowledge important for type of network feedback effectiveness? Undergraduate students in a second year Architecture Engineering course, after completing a 2-weeks long lesson on Building with Wood, were randomly assigned to a summary writing task with either Full feedback (a network with 14 central and 12 peripheral terms) or Focused feedback (a network with only the 14 central terms), and then immediately completed a knowledge structure survey. Two weeks later, they completed an End-of-Unit posttest that consisted of a Central-items and a Peripheral-items subtests. A significant interaction of feedback and domain knowledge was observed for post knowledge structure, the low domain knowledge students in the Focus feedback group had the most central link-agreement with the expert and the least peripheral links agreement. On the End-of-Unit declarative knowledge posttest, there was no difference for the Full or Focused feedback interventions, but the high domain knowledge students in both interventions performed significantly better than the low domain knowledge students on the central-items subtest butnoton the peripheral-items subtest. This investigation shows the need for further research on the role of domain-normative central concepts and pragmatically contributes to the design of essay prompts for STEM classroom use. 

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4. Using Domain-Specific, Immediate Feedback to Support Students Learning Computer Programming to Make Music

   Krug, Douglas Lusa; Zhang, Yifan; Mouza, Chrystalla; Pollock, Lori; Shepherd, David C. (January 2023, l ACM conference on Innovation and Technology in Computer Science Education (ITiCSE))

   Broadening participation in computer science has been widely stud- ied, creating many diferent techniques to attract, motivate, and engage students. A common meta-strategy is to use an outside do- main as a hook, using the concepts in that domain to teach computer science. These domains are selected to interest the student, but stu- dents often lack a strong background in these domains. Therefore, a strategy designed to increase students’ interest, motivation, and engagement could actually create more barriers for students, who now are faced with learning two new topics. To reduce this poten- tial barrier in the domain of music, this paper presents the use of automated, immediate feedback during programming activities at a summer camp that uses music to teach foundational programming concepts. The feedback guides students musically, correcting notes that are out-of-key or rhythmic phrases that are too long or short, allowing students to focus their learning on the computer science concepts. This paper compares the correctness of students that re- ceived automated feedback with students that did not, which shows the efectiveness of the feedback. Follow up focus groups with stu- dents confrmed this quantitative data, with students claiming that the feedback was not only useful but that the activities would be much more challenging without the feedback. 

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5. Insights from Student Solutions to SQL Homework Problems

   https://doi.org/10.1145/3341525.3387391  

   Poulsen, Seth; Butler, Liia; Alawini, Abdussalam; Herman, Geoffrey L. (June 2020, Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education)

   null (Ed.)

   We analyze the submissions of 286 students as they solved Structured Query Language (SQL) homework assignments for an upper-level databases course. Databases and the ability to query them are becoming increasingly essential for not only computer scientists but also business professionals, scientists, and anyone who needs to make data-driven decisions. Despite the increasing importance of SQL and databases, little research has documented student difficulties in learning SQL. We replicate and extend prior studies of students' difficulties with learning SQL. Students worked on and submitted their homework through an online learning management system with support for autograding of code. Students received immediate feedback on the correctness of their solutions and had approximately a week to finish writing eight to ten queries. We categorized student submissions by the type of error, or lack thereof, that students made, and whether the student was eventually able to construct a correct query. Like prior work, we find that the majority of student mistakes are syntax errors. In contrast with the conclusions of prior work, we find that some students are never able to resolve these syntax errors to create valid queries. Additionally, we find that students struggle the most when they need to write SQL queries related to GROUP BY and correlated subqueries. We suggest implications for instruction and future research. 

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