A DISCIPLINE OF JAVA PROGRAMMING

2011 ◽  
Author(s):  
Simone Santini
Keyword(s):  
Java Programming

Concept–based Analysis of Java Programming Errors among Low, Average and High Achieving Novice Programmers

10.28945/4246 ◽  
2019 ◽  
Keyword(s):  
Undergraduate Students ◽  
Classroom Practice ◽  
Group Discussion ◽  
Intervention Strategy ◽  
Practice Volume ◽  
Future Research ◽  
Achievement Level ◽  
Java Programming ◽  
Ability Levels ◽  
Programming Errors

[This Proceedings paper was revised and published in the 2019 issue of the Journal of Information Technology Education: Innovations in Practice, Volume 18.] Aim/Purpose: The study examined types of errors made by novice programmers in different Java concepts with students of different ability levels in programming as well as the perceived causes of such errors. Background: To improve code writing and debugging skills, efforts have been made to taxonomize programming errors and their causes. However, most of the studies employed omnibus approaches, i.e. without consideration of different programing concepts and ability levels of the trainee programmers. Such concepts and ability specific errors identification and classifications are needed to advance appropriate intervention strategy. Methodology: A sequential exploratory mixed method design was adopted. The sample was an intact class of 124 Computer Science and Engineering undergraduate students grouped into three achievement levels based on first semester performance in a Java programming course. The submitted codes in the course of second semester exercises were analyzed for possible errors, categorized and grouped across achievement level. The resulting data were analyzed using descriptive statistics as well as Pearson product correlation coefficient. Qualitative analyses through interviews and focused group discussion (FGD) were also employed to identify reasons for the committed errors. Contribution:The study provides a useful concept-based and achievement level specific error log for the teaching of Java programming for beginners. Findings: The results identified 598 errors with Missing symbols (33%) and Invalid symbols (12%) constituting the highest and least committed errors respec-tively. Method and Classes concept houses the highest number of errors (36%) followed by Other Object Concepts (34%), Decision Making (29%), and Looping (10%). Similar error types were found across ability levels. A significant relationship was found between missing symbols and each of Invalid symbols and Inappropriate Naming. Errors made in Methods and Classes were also found to significantly predict that of Other Object concepts. Recommendations for Practitioners: To promote better classroom practice in the teaching of Java programming, findings for the study suggests instructions to students should be based on achievement level. In addition to this, learning Java programming should be done with an unintelligent editor. Recommendations for Researchers: Research could examine logic or semantic errors among novice programmers as the errors analyzed in this study focus mainly on syntactic ones. Impact on Society: The digital age is code-driven, thus error analysis in programming instruction will enhance programming ability, which will ultimately transform novice programmers into experts, particularly in developing countries where most of the software in use is imported. Future Research: Researchers could look beyond novice or beginner programmers as codes written by intermediate or even advanced programmers are still not often completely error free.

Revealing And Resolving Disorientation In An Online Course Module Of Java Programming

2020 ◽  
Author(s):  
Neelma Bhatti ◽  
Imdad Ali Ismaili ◽  
Lachhman Das Dhomeja ◽  
D. Scott McCrickard
Keyword(s):  
Online Course ◽  
Java Programming

An Extension of Code Correction Problem for Java Programming Learning Assistant System

2020 ◽  
Author(s):  
Nobuo Funabiki ◽  
Masaki Yamaguchi ◽  
Minoru Kuribayashi ◽  
Htoo Htoo Sandi Kyaw ◽  
Su Sandy Wint ◽  
...  
Keyword(s):  
Java Programming ◽  
Correction Problem

scholarly journals Improving Learner-Computer Interaction through Intelligent Learning Material Delivery Using Instructional Design Modeling

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 668
Author(s):  
Christos Troussas ◽  
Akrivi Krouska ◽  
Cleo Sgouropoulou
Keyword(s):  
Instructional Design ◽  
Adaptive Learning ◽  
Educational Software ◽  
Learning Experience ◽  
Learning Material ◽  
Java Programming ◽  
Undergraduate University Students ◽  
Intelligent Tools ◽  
Content Based Filtering ◽  
Computer Interaction

This paper describes an innovative and sophisticated approach for improving learner-computer interaction in the tutoring of Java programming through the delivery of adequate learning material to learners. To achieve this, an instructional theory and intelligent techniques are combined, namely the Component Display Theory along with content-based filtering and multiple-criteria decision analysis, with the intention of providing personalized learning material and thus, improving student interaction. Until now, the majority of the research efforts mainly focus on adapting the presentation of learning material based on students’ characteristics. As such, there is free space for researching issues like delivering the appropriate type of learning material, in order to maintain the pedagogical affordance of the educational software. The blending of instructional design theories and sophisticated techniques can offer a more personalized and adaptive learning experience to learners of computer programming. The paper presents a fully operating intelligent educational software. It merges pedagogical and technological approaches for sophisticated learning material delivery to students. Moreover, it was used by undergraduate university students to learn Java programming for a semester during the COVID-19 lockdown. The findings of the evaluation showed that the presented way for delivering the Java learning material surpassed other approaches incorporating merely instructional models or intelligent tools, in terms of satisfaction and knowledge acquisition.

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