Abstract:

The sudden shift of learning using online platform has given a great impact on learners in all levels. An active learning requires full interaction between teacher and learner and that seems to scant in some online learning environments. Generally, learning computer programming is regarded as difficult, nevertheless for online learners. Many learners prefer to use emoticons and type questions or doubts rather speak up during an online session. Reading and responding to learners’ messages during an actual online learning and teaching session is a big challenge. This impedes the quality of content delivery. A single session includes the delivery of concept, syntax, semantic, example programs and tackling programming errors. Failing to respond to students’ typed questions in a timely manner may influence the learning process.

Sentiment analysis is a natural language processing technique that measure emotion suppressed in words, phrases, punctuation, and emoticon. This approach is used to observe discussion and dialogues to measure thoughts, opinions and emotions related to business, product, service, or topic. The focus of this study is to explore the common questions, doubts and emotions exhibited during an online programming course.

The participants of this study are one hundred and fifty Foundation in Engineering students who enrolled in Python programming course. The online sessions were conducted via Microsoft Teams over twelve teaching weeks. Learners typed messages includes questions and doubts directed to programming teacher, feelings expressed in words and emoticons, and chat between learners. Data was collected weekly based on the programming topics taught.

The result from this study showed learners frustration and anxiety when learning several programming concepts. However, the interest to tackle challenging programming questions seems to be evident in learners chat messages. Misconception when learning programming concepts are exhibited when writing the program, suggesting immediate feedback is crucial. The outcome of this study provides insights on the online pedagogical approaches in teaching and learning computer programming course.

Keywords:

Programming course, sentiment analysis, online learning, pedagogy.