MOOCs, Completion Rate, Learning Satisfaction, Quantity and Quality of the Knowledge

This study uses TAM theory to better understand variables that are indicative of MOOCs’ courses’ completion rates; furthermore, this paper scrutinizes the quantitative relationship between MOOC platform usage and learning satisfaction.

This research was an applied research and the place of the research was in a virtual community called Coursera and people all over the word participated in this community. The research design was quantitative and the questionnaire link was posted on the Coursera and sampling method was based on convenience. Data collection process started from November 12, 2020 until February 23, 2021 and 234 users of the selected MOOC platform (Coursera) participated to evaluate the proposed model. A multivariable systematic technique (PLS) applied to analysis the model. To conduct the reliability test, individual item loadings and internal consistency were used. Convergent validity of the model was measured using the Structural Equation Model (SEM). The examination of the SEM incorporated an evaluation of the path coefficients and R2 values.

The loadings of all measurement items are more than 0.792. This proves that the dataset has sound internal reliability. Moreover, the Cronbachchr(chr(chr('39')39chr('39'))39chr(chr('39')39chr('39')))s alpha values are all > 0.7 which proves the internal consistency of the research model. In this research, the range of CR is 0.838 to 0.947 and the range of AVEs is 0.634–0.857, both exceed the threshold values for desirable convergent validity. To obtain discriminant validity, the square root of AVE should be more than the correlations among the constructs. The value of each AVE’s square root is greater than the off-diagonal components. The model explains 21.1% of the variance in perceived usefulness, 20.9% in perceived ease of use, 26.9% in attitude to use, 20.0% in MOOC platform actual usage and 24.2% of the variance in learning satisfaction. The path coefficient from quantity and quality of knowledge (β=0.261, p<0.01) and perceived feedback (β=0.215, p<0.01) to PU is positive. The results show that perceived feedback (β=0.275, p<0.01), perceived complexity (β=-0.367, p<0.01) significantly and meaningfully affect PEOU. The PU showed a positive and strong effect on attitude to use (β=0.271, p<0.01), MOOC platform actual usage (β=0.360, p<0.01), and learning satisfaction (β=0.277, p<0.01).

The results indicated that the quantity and quality of the knowledge and perceived feedback have a positive and significant impact on the perceived usefulness of MOOCs. The perceived complexity as a negative construct was found to be an important indicator of MOOC platforms usage and the hypothesis regarding the platform usage and learning satisfaction was upheld.