Diagnosing Student Learning Problems in Object Oriented Programming

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.

Call for papers Journal of Control Theory and Applications Special issue on Approximate dynamic programming and reinforcement learning

Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain and nonconvex environments over time.

MET as Program Resources for College English Teaching and Learning：Application and Implications

This paper investigates the current situation of Modern Educational Technology （MET） as program resources for college English teaching, exploring the effectiveness of the integration of MET and language teaching and learning. The case study in this paper illustrates that MET does benefit college English teaching but there are many problems of its application. Pedagogical implications are then provided to enhance the effective integration of MET and language teaching and learning： （1） it is wise for the teachers and learners to reconcile what is desirable with what is acceptable and possible in MET application; （2） teachers should optimize other existing resources to solve the problems caused by inequality and unavailability of MET; （3） teachers should have a clear conception of the relationship of MET and pedagogy to design and apply courseware appropriately; （4） students have beliefs in the benefits of MET, resulting in enhancing their individual language learning and efficiency.

Time Prediction Model of Personalized Affective Support Based on the Programming Process

In online programming education,if teachers can determine any difficulties their students are experiencing and provide support,it would significantly improve the outcome of their teaching.This paper describes an attempt to build a time prediction model on the demand for personalized affective support based on a modified version of the Synthetic Minority Over-sampling Technique.We designed and conducted a data collection experiment based on the specific features of the affective support.Meanwhile,the modified oversampling algorithm can ascertain the time for providing such support for learners,which solves the problem of a class imbalance distribution.In addition,we obtained a sorting algorithm of the time prediction regarding the demand for personalized affective support in programming learning and constructed a time prediction model on the demand for affective support.Meanwhile,we conducted experiments on both public data and our own collected data to verify the effectiveness of the constructed model.The results show that the model is able to judge whether learners need affective support during the writing code process.

Learning control of fermentation process with an improved DHP algorithm

Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.