Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial ...Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial step in understanding their current programming situation and implementing appropriate instructional interventions.However,how to detect students’programming difficulties accurately without students’awareness remains a big challenge.Address the issues above;this paper adopts a sensor-free difficulties detecting method based on a deep neural network which employs a recurrent neural network(RNN)model and uses the sequential timing data from programming behaviour.The method can detect students’programming difficulties in real-time with 93%accuracy without interference in the programming process.In the long term,this method is the first step for establishing an automated intelligent programming environment.At the same time,it can assist teachers in noticing the difficulties that students encounter.Then,teachers can adjust their teaching plans and provide manual tutoring intervention more quickly.展开更多
Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of pr...Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of programming in higher education. In this paper, the authors propose an Object Oriented conceptual map model and organize this approach into three levels： constructing a Concept Effect Propagation Table, constructing Test Item-Concept Relationships and diagnosing Student Learning Problems with Matrix Composition. The authors＇ work is a modification of the approaches of Chert and Bai as well as Chu et al., as the authors use statistical methods, rather than fuzzy sets, for the authors＇ analysis. This paper includes a statistical summary, which has been tested on a small sample of students in King Abdulaziz University, Jeddah, Saudi Arabia, illustrating the learning problems in an Object Oriented course. The experimental results have demonstrated that this approach might aid learning and teaching in an effective way.展开更多
基金supported by the 2018-2020 Higher Education Talent Training Quality and Teaching Reform Project of Sichuan Province(Grant No.JG2018-46)the Science and Technology Planning Program of Sichuan University and Luzhou(Grant No.2017CDLZG30)the Postdoctoral Science fund of Sichuan University(Grant No.2019SCU12058).
文摘Programming difficulties are one of the common problems faced by software engineering students,which can lead to a rapid decline in motivation and even drop out.Probing students’programming difficulties is a crucial step in understanding their current programming situation and implementing appropriate instructional interventions.However,how to detect students’programming difficulties accurately without students’awareness remains a big challenge.Address the issues above;this paper adopts a sensor-free difficulties detecting method based on a deep neural network which employs a recurrent neural network(RNN)model and uses the sequential timing data from programming behaviour.The method can detect students’programming difficulties in real-time with 93%accuracy without interference in the programming process.In the long term,this method is the first step for establishing an automated intelligent programming environment.At the same time,it can assist teachers in noticing the difficulties that students encounter.Then,teachers can adjust their teaching plans and provide manual tutoring intervention more quickly.
文摘Students often face difficulties while taking basic programming courses due to several factors. In response, research has presented subjective assessments for diagnosing learning problems to improve the teaching of programming in higher education. In this paper, the authors propose an Object Oriented conceptual map model and organize this approach into three levels： constructing a Concept Effect Propagation Table, constructing Test Item-Concept Relationships and diagnosing Student Learning Problems with Matrix Composition. The authors＇ work is a modification of the approaches of Chert and Bai as well as Chu et al., as the authors use statistical methods, rather than fuzzy sets, for the authors＇ analysis. This paper includes a statistical summary, which has been tested on a small sample of students in King Abdulaziz University, Jeddah, Saudi Arabia, illustrating the learning problems in an Object Oriented course. The experimental results have demonstrated that this approach might aid learning and teaching in an effective way.
