The Use of Python Tutor on Programming Laboratory Session: Student Perspectives

Based on the fact that the impact of educational tools can only be accurately measured through student-centered evaluation, this paper proposes a long-term in-class evaluation for Python Tutor, a program visualization tool developed by Guo. The evaluation involves 53 students from 4 Basic Data Structure classes, which were held in the even semester of 2016/2017 academic year. It is conducted based on questionnaire survey asked to the students after they have used Python Tutor in their half of programming laboratory sessions. In general, there are three findings from this work. Firstly, Python Tutor helps students to complete programming laboratory tasks, specifically for Basic Data Structure material. Secondly, Python Tutor helps students to understand general programming aspects which are execution flow, variable content change, method invocation sequence, object reference, syntax error, and logic error. Finally, based on student perspectives, Python Tutor is a helpful tool positively affecting the students

Sistem Pakar Berbasis Web sebagai Alat Bantu Pembelajaran Mahasiswa Kedokteran untuk Penyakit Kanker Darah pada Anak

Today,expert system as a part of artificial intelligence has many applications in various fields. This report presents one of expert system applications, namely health problemsknowledge base. Specifically, the final project presented here applies expert system approach to the knowledge base of blood cancer disease in children. It is expected to helpmedical practitioners and students to improve their quality of learning and knowledge. Features of the application are disease definitions, explanations and consultations. There isalso a facility to add, delete and update the knowledge base. Knowledge base is implemented using a decision tree, which consists of rules governed by forward chaining inference technique. This application is coded using PHP and MySQL

The Effectiveness of a Program Visualization Tool on Introductory Programming: A Case Study with PythonTutor

Program Visualization (PV) is an educational tool frequently used to assist users for understanding a program flow. However, despite its clear benefits, PV cannot be incorporated easily on Introductory Programming course. Several key properties such as student characteristics and behavior should be considered beforehand. This paper is intended to provide an empirical review about the impact of PV toward students of Introductory Programming course. For our case study, PythonTutor is selected as a sample of PVs due to its accessibility. It can be accessed anywhere and anytime through a web browser. Three conclusions are obtained based on our evaluation on data collected from a survey. Firstly, PV is quite effective to assist students for conducting several programming sub-tasks. Secondly, PV, at some extent, may help students to learn advanced topics on Introductory Programming course. Finally, despite the fact that several features should be incorporated to enhance understanding of students, PV is beneficial for learning Introductory Programming course, especially when it is frequently used

Combining program visualization with programming workspace to assist students for completing programming laboratory task

Numerous Program Visualization tools (PVs) have been developed for assisting novice students to understand their source code further. However, none of them are practical to be used in the context of completing programming laboratory task; students are required to keep switching between PV and programming workspace since PV’s features are considerably limited for developing programming solution from scratch. This paper combines PV with programming workspace to handle such issue. Resulted tool (which is named PITON) has 13 features extracted from PythonTutor (a program visualization tool), PyCharm (a programming workspace), and student’s feedbacks about PythonTutor. According to think-aloud and user study, PITON is more practical to be used than a combination of PythonTutor and PyCharm. Further, its features are considerably helpful; students rated these features as useful and frequently usedPeer Reviewe

Bloom-epistemic and sentiment analysis hierarchical classification in course discussion forums

Online discussion forums are widely used for active textual interaction between lecturers and students, and to see how the students have progressed in a learning process. The objective of this study is to compare appropriate machine-learning models to assess sentiments and Bloom’s epistemic taxonomy based on textual comments in educational discussion forums. The proposed method is called the hierarchical approach of Bloom-Epistemic and Sentiment Analysis (BE-Sent). The research methodology consists of three main steps. The first step is the data collection from the internal discussion forum and YouTube comments of a Web Programming channel. The next step is text preprocessing to annotate the text and clear unimportant words. Furthermore, with the text dataset that has been successfully cleaned, sentiment analysis and epistemic categorization will be done in each sentence of the text. Sentiment analysis is divided into three categories: positive, negative, and neutral. Bloom’s epistemic is divided into six categories: remembering, understanding, applying, analyzing, evaluating, and creating. This research has succeeded in producing a course learning subsystem that assesses opinions based on text reviews of discussion forums according to the category of sentiment and epistemic analysis

Utilising pair programming to enhance the performance of slow-paced students on introductory programming

Due to its high failure rate, Introductory Programming has become a main concern. One of the main issues is the incapability of slow-paced students to cope up with given programming materials. This paper proposes a learning technique which utilises pair programming to help slow-paced students on Introductory Programming; each slow-paced student is paired with a fast-paced student and the latter is encouraged to teach the former as a part of grading system. An evaluation regarding that technique has been conducted on three undergraduate classes from an Indonesian university for the second semester of 2018. According to the evaluation, the use of pair programming may help both slow-paced and fast-paced students. Nevertheless, it may not significantly affect individual academic performancePeer Reviewe

The impact of developing a blended learning sub-system on students online learning engagement

In this research, we show a development process of engagement sub-systems in a blended-learning management system and evaluate the impact of student interaction in the whole system. We develop special sub-systems for engagement purposes via forum, course rating, and class assignment modules. During the system development process, we employ continuous improvement methodology which helps to shorten the software delivery time without disturbing the overall operation. We evaluate the impact of engagement processes in terms of behavioral, emotional and cognitive aspects. Our evaluation results show that by employing the engagement sub-systems we have increased a 0.30 satisfaction point on average (1-5 Likert scale) for 11 evaluation survey questions distributed to 305 students during 2 times evaluation period. Another interesting finding from the surveys is that behavioral (discussion forum and attendance list sub-system) and cognitive (course rating sub-system) aspects have great influences for the students’ activities (class assignment sub-system) which finally has a great impact on their cognitive performancesPeer Reviewe