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This paper aims to investigate the relationship between the students’ digital activities and their academic performance through two stages. In the first stage, students’ digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the significance of the relationship between these profiles and the associated academic performance was tested statistically.

The LMS delivers E-learning courses and keeps track of the students’ activities. Investigating these students’ digital activities became a real challenge. The diversity of students’ involvement in the learning process was proven through the LMS which characterize students’ specific profiles. The Educational Data Mining (EDM) approach was used to discover students’ learning profiles and associated academic performances, where the activity log file exemplified their activities hosted in the LMS. The sample study data is from an undergraduate e-course hosted on the platform of Blackboard LMS offered at a Saudi University during the first semester of the 2019–2020 academic year. The chosen undergraduate course had 25 sections, and the students attending came from science, technology, engineering and math background.

Results show three clusters based on the digital activities of the students. The correlation test shows the statistical significance and proves the effect of the student’s profile on his academic performance. The data analysis shows that students with different profiles can still get similar academic performance using LMS.

This empirical study emphasizes the importance of the EDM approach using clustering techniques which can help the instructor understand how students use the provided LMS content to learn and then can deliver them the best educational experience.

The objective of this study is to investigate the key determinants affecting the acceptance and utilization of Blackboard as a Computer-Assisted Language Learning (CALL) platform among Saudi university students pursuing English as a foreign language (EFL) courses.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The study's findings indicate that performance expectancy, social influence, effort expectancy and price value significantly affect the attitudes of EFL students toward using CALL. The habit factor was the most robust predictor of behavioral intention and technology use, indicating that CALL usage can become automatic for students and improve their engagement in EFL learning. The study highlights the importance of providing better technical and organizational support to EFL students who want to use CALL more effectively. The theoretical and practical implications of the study's findings are thoroughly discussed.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the UTAUT2 by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The purpose of this paper is to check the feasibility of using biomaterial such as of Phragmites-Australis (PA) in cement paste to achieve sustainable building materials.

In this study, cement pastes were prepared by adding locally produced PA fibers in four different volumes: 0%, 0.5%, 1% and 2% for a duration of 180 days. Bottles and prisms were subjected to chemical shrinkage (CS), drying shrinkage (DS), autogenous shrinkage (AS) and expansion tests. Besides, prism specimens were tested for flexural strength and compressive strength. Furthermore, a mathematical model was proposed to determine the variation length change as function of time.

The experimental findings showed that the mechanical properties of cement paste were significantly improved by the addition of 1% PA fiber compared to other PA mixes. The effect of increasing the % of PA fibers reduces the CS, AS, DS and expansion of cement paste. For example, the addition of 2% PA fibers reduces the CS, expansion, AS and DS at 180 days by 36%, 20%, 13% and 10%, respectively compared to the control mix. The proposed nonlinear model fit to the experimental data is appropriate with R2 values above 0.92. There seems to be a strong positive linear correlation between CS and AS/DS with R2 above 0.95. However, there exists a negative linear correlation between CS and expansion.

The PA used in this study was obtained from one specific location. This can exhibit a limitation as soil type may affect PA properties. Also, one method was used to treat the PA fibers.

The utilization of PA fibers in paste may well reduce the formation of cracks and limit its propagation, thus using a biomaterial such as PA in cementitious systems can be an environmentally friendly option as it will make good use of the waste generated and enhance local employment, thereby contributing toward sustainable development.

To the authors best knowledge, there is hardly any research on the effect of PA on the volume stability of cement paste. Therefore, the research outputs are considered to be original.