Assessment of Academic Performance with The E-mental Health Interventions in Virtual Learning Environment Using Machine Learning Techniques: A Hybrid Approach

Background: The act of virtual learning is defined through learning and practicing in an environment using digital/electronic content for self-paced through online teaching and mentoring. It explicitly deals with the interaction in an asynchronous mode of learning. The quality of teaching-learning depends on the utilization of digital technologies with the advancement in educational technology. There is a need and evaluation for the assessment and estimation of the impact of e-mental health interventions with the students learning through the virtual learning environment.

Purpose/Hypothesis: This research evaluates the psychotherapeutic support for the students to overcome the psychological distress during this COVID-19 pandemic by using machine learning techniques. This mechanism evaluates the efficacy of the academic performance made by the students during the pandemic situation. This analysis involves a hybrid approach for the assessment in machine learning using a genetic algorithm with an artificial neural network upon statistical evaluation. The psychological factors are determined with a keen focus on behaviourism, cognitivism, and social constructivism. The metrics have been evaluated based on digital technologies (ICT) in remote access, individual learning process, flexible learning, cost-effectiveness, time complexity and scalability.

Design/Method: The design process involves the 775 student responses with 27 attributes with differentiation of labels corresponding to behaviourism, cognitivism, and social constructivism. The preprocessed data is fed to genetic algorithm with processing parameters focusing crossover and mutation probability and then classified using artificial neural network. The estimation of academic performance is made using the techniques followed in virtual learning environment such as:

1. Online quiz (Quizizz platform) – Individual assessment

2. Flipped classroom activity - Individual assessment

3. MOOCs online courses – Individual assessment

4. Prototype design – Team activity

5. Research proposal – Team activity

From the assessment process the each of the student performance is evaluated with regard to the course outcome of individual student in the learning environment. The variation has also been observed with the applicability of ALS and traditional practice methods.

Results: The hybrid approach found to be good in the assessment and evaluation of academic performance and health interventions in terms of accuracy (88.18%), precision (94.69%), recall (92.24%), RMS error (0.202) and correlation (0.844) respectively. The statistical analysis and evaluation have been made using Fisher's F-Statistical test, and the P-value is found significantly to be P<0.001. From the experiments, the factors that contribute towards web-based learning, blended learning, and online learning has been differentiated with the psychotherapeutic factors. A total of 775 samples have been used for analysis with the applicability of ICT tools and the pedagogical practices for the course. The factors contributing towards Behaviorism with a focus on interaction and response towards the learning environment plays a significant role in varying the academic performance of the student of about 20% in total learning rate varied significantly. Step-by-step analysis in virtual learning provides a good initiative for the student's community to have a variation in the learning process. Virtual learning is one of the good practices if the ICT in education, process and its principles adhere more efficiently.