Quality Model for Massive Open Online Course (MOOC) Web Content

With the philosophy of providing open education to all, Massive Open Online Course (MOOC), which introduced in 2006, has been through its first decade. Despite its popularity and worldwide acceptance, MOOC faces a few criticisms about the weaknesses of its content such as lack of clarity, unstructured, poor design and lack of fundamental initial requirements. This caused by the paucity of understanding among content providers about the facet of qualities contributes to the content. There are some previous efforts to improve the quality of MOOCs, but none focused on the content from the content providers or experts' view. As a result, most of the vital internal quality factors are neglected. Besides, the operational definition for the MOOC content quality factors is still missing or not well-defined. Therefore, this research proposes a quality model for MOOC web content as a content provider’s reference to develop quality MOOC content. In order to achieve that, three basic elements were implemented which is the content’s provider perspective, MOOC content quality dimensions and MOOC content quality factors. Development of MOOC content quality dimension is based on 7C’s model and PDCA for continuity, while the determination of factors involves the process like a revision of the possible factors from literature, factors combination and categorization. This proposed hierarchical model tends to make MOOC's learning more optimistic and beneficial to the learners through the development of high-quality content

Web content quality model for massive open online course

Despite its popularity and acceptance since introduced in 2008, the Massive Open Online Course (MOOC) has faced a number of criticisms regarding its content weaknesses such as lack of clarity, unstructured, poor design and ignorance of learner’s diversity. This is due to the lack of understanding among content providers about the quality aspects that contribute to web content. There are number of previous efforts to improve the quality of MOOC, but none were focused on the web content quality from the view of content providers or experts. As a result, most of the internal quality factors were neglected while the operational definition for the MOOC content quality factors is not well-defined. Therefore, this research proposes a web content quality model for MOOC to be referred by the content provider to develop quality MOOC content. In addition, it is as guidance to determine the quality of a MOOC web content. The model which is based on 7C’s Model for Learning Design Framework was initially developed with the determination of quality factors derived from content analysis involving systematic review on literatures, quality factors combination and categorization. The model was then validated by content providers and experts, which involved content validity test, pretesting and survey on acceptability. Data was analyzed using the Rasch Model on its ability to simplify measurement by converting ordinal data to intervals, besides anticipates data fitness statistically. The analysis showed that 52 quality factors along with nine categories were accepted in determining the web content quality for MOOC. In order to measure the model acceptance in a real-world application, the tool which automates the analysis and evaluation of the web content quality for MOOC based on the quality model was developed named MOOC Content Quality Assessment Tool (MOCQAT). MOCQAT was utilized by 42 stakeholders in UPSI as a case study before their acceptance was confirmed through the technology acceptance test. As a contribution, this research produced a comprehensive web content quality model for MOOC along with the definitions and measurement attributes from the perspective of content providers and experts, which is the first to be developed. The acceptability of the model by stakeholders is also proven by the development and technology acceptance test of MOCQAT

Analysis of web content quality factors for massive open online course using the Rasch model

The lack of understanding among content providers towards the quality of MOOC motivates the development of several MOOC quality models. However, none was focused on the web content from the perspective of content providers or experts despite the facts that their views are important particularly in the development phase. MOOCs learners and instructors definitely understand the functional external quality, but content providers have better understanding to the internal qualities, which is required during the development phase. The initial quality model for MOOC web content based on 7C’s of Learning Design and PDCA model for continuity have been proposed, consisted of nine categories and 54 factors. This research focuses on the validation towards the proposed model by content providers and experts to provide systematic evidence of construct validity. This involved two main processes; content validity test and survey on acceptability. The content validity test was conducted to confirm the agreeability of proposed categories and factors among respondents. The Dichotomous Rasch model was utilized to explain the conditional probability of a binary outcome, given the person's agreeability level and the item's endorsability level. Subsequently, the survey on acceptability was conducted to obtain confirmation and verification from the experts group pertaining on MOOC web content quality factors. Rasch Rating Scale model was used since it specifies the set of items, which share the same rating scale structure. The usage of the Rasch Model in instrument development generally ease variable measurement by converting the nonlinear raw data to linear scale, while assists researchers in tackling fitness validation and other instrumentation issues like person reliability and unidimensionality. This paper demonstrates the strengths of applying Rasch Model in construct validation and instrument building, which provides a strong foundation for the model adaptation as a methodological tool