Grounded theory methodology (GTM) is an extensive research methodology that is immensely active in numerous social science research fields. It is by far one of the most popular techniques applied in qualitative research. The challenge in using such methods might appear in their complexity. Several steps of coding and analysis in GTM can be fuzzy and multifaceted for novice researchers specialised in Information Systems (IS) fields, knowledge management, and broad applications of IS. The current study suggests a design framework for novices in qualitative research that presents GTM as a set of techniques characterised graphically, allowing the extraction of grounded results and a set of pragmatic analysed data classifications rather than only concentrating on implementing a grounded “theory”. Hence, the research stresses using the term “grounded techniques”, permitting the creation of grounded categories to strengthen qualitative research results' rigour. The proposed framework meticulously exemplifies how an organised set of phases in a research design can enlighten the novice researcher while conducting a study in knowledge absorptive capacity using a comprehensive GTM process to enforce the understanding of GTM techniques.

This study technically analyses one of the online exam supervision technologies, namely the Artificial Intelligence-based Auto Proctoring (AiAP). This technology has been heavily presented to the academic sectors around the globe. Proctoring technologies are developed to provide oversight and analysis of students’ behavior in online exams using AI, and sometimes with the supervision of human proctors to maintain academic integrity in a blended format. Manual Testing methodology was used to do a software testing on AiAP for verification of any possible incorrect red flags or detections. The study took place in a Middle Eastern university by conducting online exams for 14 different courses, with a total of 244 students. Afterward, five human proctors were assigned to verify the data obtained by the AiAP software. The results were then compared in terms of monitoring measurements: screen violation, sound of speech, different faces, multiple faces, and eyes movement detection. The proctoring decision was computed by averaging all monitoring measurements and then compared between the human proctors’ and the AiAP decisions, to ultimately set the AiAP against a benchmark (human proctoring) and hence to be viable for use. The decision represented the number of violations to the exam conditions, and the result showed a significant difference between Human Decision (average 25.95%) and AiAP Decision (average 35.61%), and the total number of incorrect decisions made by AiAP was 74 out of 244 exam attempts, concluding that AiAP needed some improvements and updates to meet the human level. The researchers provided some technical limitations, privacy concerns, and recommendations to carefully review before deploying and governing such proctoring technologies at institutional level. This paper contributes to the field of educational technology by providing an evidence-based accuracy test on an automatic proctoring software, and the results demand institutional provision to better establish an appropriate online exam experience for higher educational institutions.

This research aims to investigate the direct and formal effect of visual aesthetics on customers’ willingness to participate in an online marketing campaign, given that visual aesthetics is considered a salient design characteristic that customers tend to refer to when expressing their experience with the online retailer environment. This research study incorporates the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM) to propose and estimate this direct effect through structural aesthetics TAM model. In order to validate the proposed model, an online survey with interactive experience was constructed utilizing an open-source platform and was primarily sent to scholars specializing in HCI, informatics, user experience, and digital marketing research in the United Kingdom. The data were obtained from 360 participants, and Partial Least Squares (PLS) path modeling using SmartPLS 4 was employed to evaluate the proposed model. The empirical evaluation demonstrated and confirmed the authenticity and novelty of significant direct and formal effects of customers’ perceived visual aesthetics on their willingness to participate in an online marketing campaign (β = 0.462, t = 10.847, p < 0.001), and their usage attitude (β = 0.789, t = 39.622, p < 0.001). These findings highlight the importance of visual aesthetics in online marketing campaign design, suggesting that concise, well-organized, and visually appealing user interfaces is more likely to engage customers than a complex, cluttered one.

This paper contributes to advancing qualitative and mixed-methods research in business by offering a comprehensive framework that rigorously validates qualitative findings through an explanatory sequential mixed-methods approach. Qualitative research broadly investigates and exposes facts from an epistemological perspective. However, challenges related to the generalisation and validity of the qualitative results require further inquiry, specifically in computer science and business technology research, such as business data analytics. Thus, this article aims to guide researchers in sequentially validating qualitative research methods using Grounded Theory Methodology GTM, bias reduction, and Structural equation modelling (SEM). The study suggests three sequential stages of mixed-methods research design — the research methods employed (GTM) to extract qualitative categories. Data was collected from postgraduate students using semi-structured interviews that were analysed using a rigorous (GTM) coding technique. Accordingly, results underwent a process of bias reduction as an initial phase of validation of qualitative results, and finally, results were validated using quantitative SEM analysis. The proposed framework meticulously demonstrates how an ordered set of stages in a research design can validate qualitative results while steering a study in conceptualising Business Analytics (BA) as an academic field. The research makes significant contributions to the practical and theoretical implications of qualitative results, mixed methods research design, and validation processes in business computing education research fields, thereby enhancing the understanding and application of these methods in real-world scenarios.