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检索条件"主题词=programming process data"
16 条 记 录,以下是11-20 订阅
Time-on-Task Metrics for Predicting Performance  2022
Time-on-Task Metrics for Predicting Performance
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53rd Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)
作者: Leinonen, Juho Castro, Francisco Enrique Vicente Hellas, Arto Aalto Univ Espoo Finland Univ Massachusetts Amherst Amherst MA USA
Time-on-task is one key contributor to learning. However, how timeon-task is measured often varies, and is limited by the available data. In this work, we study two different time-on-task metrics-derived from programm... 详细信息
来源: 评论
The Effects of Compilation Mechanisms and Error Message Presentation on Novice Programmer Behavior  20
The Effects of Compilation Mechanisms and Error Message Pres...
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51st ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)
作者: Karvelas, Ioannis Li, Annie Becker, Brett A. Univ Coll Dublin Dublin Ireland Univ Michigan Ann Arbor MI 48109 USA
It is generally accepted that learning to program could be easier for many students. One of the most important components of this experience is the programming environment. Novices learn in a variety of environments, ... 详细信息
来源: 评论
Student Modeling Based on Fine-Grained programming process Snapshots  17
Student Modeling Based on Fine-Grained Programming Process S...
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13th ACM Conference on International Computing Education Research (ICER)
作者: Leinonen, Juho Univ Helsinki Helsinki Finland
I am studying the use of fine-grained programming process data for student modeling. The initial plan is to construct different types of program state representations such as Abstract Syntax Trees (ASTs) from the data... 详细信息
来源: 评论
Factors Affecting Compilable State at Each Keystroke in CS1  23
Factors Affecting Compilable State at Each Keystroke in CS1
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IEEE/ACM 45th International Conference on Software Engineering - Software Engineering Education and Training (ICSE-SEET)
作者: Scott, Steven Hellas, Arto Leinonen, Juho Edwards, John Utah State Univ Dept Comp Sci Logan UT 84322 USA Aalto Univ Dept Comp Sci Espoo Finland
In this paper, we analyze keystroke log data from two introductory programming courses from two distinct contexts to investigate the proportion of events that compile, how this relates to contextual factors, the progr... 详细信息
来源: 评论
G is for Generalisation: Predicting Student Success from Keystrokes  2023
G is for Generalisation: Predicting Student Success from Key...
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54th Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS)
作者: Pullar-Strecker, Zac Pereira, Filipe Dwan Denny, Paul Luxton-Reilly, Andrew Leinonen, Juho Univ Auckland Auckland New Zealand Univ Fed Roraima Boa Vista Parana Brazil Aalto Univ Espoo Finland
Student performance prediction aims to build models to help educators identify struggling students so they can be better supported. However, prior work in the space frequently evaluates features and models on data col... 详细信息
来源: 评论
Compile Much? A Closer Look at the programming Behavior of Novices in Different Compilation and Error Message Presentation Contexts  20
Compile Much? A Closer Look at the Programming Behavior of N...
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2020 Conference on United Kingdom and Ireland Computing Education Research
作者: Karvelas, Ioannis Dillane, Joe Becker, Brett A. Univ Coll Dublin Dublin Ireland
Learning to program is a process that relies on learning theoretical fundamentals as well as practice, and almost always involves some type of programming environment. In order to build effective environments that sup... 详细信息
来源: 评论