Learning Analytics: Virtual Reality for Programming Course in Higher Education

The conventional teaching styles are monotonous and fail to help all the levels of the students to achieve the expected competencies of the course; thereby lack the motivation. With the advancement of educational technology and the urge to engage learners of the 21st century, it is necessary to shift the classroom paradigm of higher education embedded with the new innovative teaching styles. With the use of ICT for education, the teaching-learning processes are streamlined with smart classrooms equipped with collaborative activities and the course instructors take advantage of available free online ICT tools and cloud services for higher education. The courses like mathematics, programming language and algorithms are very challenging for the students of computer science engineering and even for the students of other departments. To provide better teaching strategies for addressing this challenge, the objective of this ongoing project is to adopt VR for teaching programming courses. The first-year undergraduate students from all the departments practice common Python course with the same teaching style and assessment pattern. This course teaching style includes traditional classroom teaching embedded with practice questions for each topic in the laboratory. To explore the new teaching style, a Virtual Reality mobile game is introduced to the learners of the first year. Few sessions experimented with the virtual reality mobile app for assessing the cognitive level of the students in the Python course. This virtual reality mobile app is designed with a maze game pattern of three stages. The learners need to find all the right doors to open the path inorder to reach the final place. Each door is embedded with challenging time-based Python questions that are arranged in the form of random activities like complete code, debugging, jumble code and drag & drop. All the activities are given scores based on the correct answers and wrong answers will reduce the timer for solving the questions. Each stage has variations with easy, medium and expert levels. The higher levels are entrenched with more challenging activities with higher-order thinking. The students are motivated to learn Python programming in the form of virtual reality mobile games. The final score determines the level of the learners and the cognitive skills acquired in this course. This type of teaching-learning style will also help the course instructors to identify the slow learners who score less marks in all the levels or many attempts. This technique uses MALAR rubrics for PCC model as an evaluation pattern in the course. The MALAR rubrics include identifying the problem solving, creative thinking and critical thinking skills of the learners. The limitations with the adoption of this strategy is to ensure the use of VR based console in the classroom or rent it for the students as these activities cannot be experienced without VR console. The cumulative scores of the students are analyzed using a reinforcement learning technique. The reward points are given to the learners based on the successful attempt of solving the Python questions and every unsuccessful attempt will add negative scores. The overall mark determines the award points of the learners. The cognitive levels of the learners are analyzed using the learning analytics like the clustering algorithm. This clustering algorithm is framed by using rubrics score and reinforcement rewards points. This analysis helps the faculty to understand the cognitive level of the learners, competency skills, emotions of the learners of adopting VR techniques and slow learners in the Python course.