ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Thu 18 Apr 2024 11:30 - 11:45 at Glicínia Quartin - Dependability and Formal methods 2 Chair(s): Jácome Cunha

Background: Many programming environments include automated feedback in the form of hints to help novices learn programming autonomously. Some experimental studies investigated the impact of automated hints in the immediate performance and learning retention in that context. Automated feedback is also becoming a popular research topic in the context of formal specification languages, but so far no experimental studies have been conducted to assess the impact of hints while learning such languages. Objective: We aim to investigate the impact of different types of automated hints while learning a formal specification language, not only in terms of immediate performance and learning retention, but also in the emotional response of the students. Method: We conducted a simple one-factor randomised experiment in 2 sessions involving 85 undergraduate students majoring in computer science and engineering. In the 1st session students were divided in one control group and three experimental groups, each receiving a different type of hint while learning to specify simple requirements with the Alloy formal specification language. To assess the impact of hints on learning retention, in the 2nd session, 1 week later, all students had no hints while formalising requirements. Before and after each session the students answered a standard self-reporting emotional survey to assess their emotional response to the experiment. Results: Of the three types of hints we evaluated, only the ones that point to the precise location of an error had a positive impact on the immediate performance and none of them had significant impact in the learning retention. Hint availability also causes a significant impact on the emotional response, but no significant emotional impact exists once hints are no longer available (e.g. no significant deprivation effects were detected). Conclusion: Although none of the evaluated hints had an impact on learning retention, learning a formal specification language with an environment that provides hints with precise error locations seems to contribute to a better overall experience without apparent drawbacks. Further studies are needed to investigate if other kinds of hints, namely hints combined with some sort of self-explanation prompts, can have a positive impact in learning retention.

Thu 18 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
Dependability and Formal methods 2Research Track / Software Engineering Education and Training / Demonstrations / Software Engineering in Practice at Glicínia Quartin
Chair(s): Jácome Cunha University of Porto & HASLab/INESC
11:00
15m
Talk
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning
Research Track
Pingchuan Ma HKUST, Zhenlan Ji The Hong Kong University of Science and Technology, Peisen Yao Zhejing University, Shuai Wang The Hong Kong University of Science and Technology, Kui Ren Zhejiang University
11:15
15m
Talk
Translation Validation for JIT Compiler in the V8 JavaScript Engine
Research Track
11:30
15m
Talk
Assessing the impact of hints in learning formal specification
Software Engineering Education and Training
Alcino Cunha University of Minho; INESC TEC, Nuno Macedo University of Porto; INESC TEC, José Creissac Campos University of Minho & HASLab/INESC TEC, Iara Margolis Center for Computer Graphics, Emanuel Sousa Center for Computer Graphics
11:45
15m
Talk
GWP-ASan: Sampling-Based Detection of Memory-Safety Bugs in Production
Software Engineering in Practice
12:00
15m
Talk
Dynamic Alert Suppression Policy for Noise Reduction in AIOps
Software Engineering in Practice
karan bhukar IBM Research, Harshit Kumar IBM Research, Ruchi Mahindru IBM Research, Rohan Arora IBM Research, Seema Nagar IBM Research, Pooja Aggarwal IBM Research, Amit Paradkar IBM Watson Research Center
12:15
7m
Talk
What Do You Mean by Memory? When Engineers Are Lost in the Maze of Complexity
Software Engineering in Practice
Gunnar Kudrjavets Amazon Web Services, USA, Aditya Kumar Google, Jeff Thomas Meta Platforms, Inc., Ayushi Rastogi University of Groningen, The Netherlands
DOI Pre-print
12:22
7m
Talk
SpotFlow: Tracking Method Calls and States at Runtime
Demonstrations
Pre-print Media Attached