Wejdan Farhan received her Master’s in Computational Science and PhD in Interdisciplinary Studies of Human-Computer Interaction from Laurentian University in Canada. She has been teaching at the university level for over 10 years. She has worked in public and private universities in Jordan, Saudi Arabia and the United Arab Emirates (UAE). In the UAE, she joined Al Ain University as an Assistant Professor in the Department of Management Information Systems (MIS) in the College of Business. Her teaching interests include web applications, programming language, database management systems and system analysis and design. Her primary research interests are in the field of human-computer interaction, specifically, e-learning and in e-health applications. She has published in refereed journals indexed in Scopus and the ABDC list such as Technology in Society, Disability and Rehabilitation: Assistive Technology and International Journal of Medical Informatics.
PhD, Human-Computer Interaction, Laurentian University, Canada.
Master, Computational Science, Laurentian University, Canada.
Bachelor in Computer Science, Al-Zaytoonah University, Jordan
Human-Computer Interaction: E- learning systems and E-health applications.
- Razmak, J., Farhan, W., & and El Refae, G. (2021). Proposing new innovative technological features to support human e-learning interaction processes in academic organizations, Int. J. Technology Enhanced Learning, Forthcoming.
- Farhan, W., & Razmak, J. (July 2020). A comparative study of an assistive e-learning interface among students with and without visual and hearing impairments, Disability and Rehabilitation: Assistive Technology, 1-11.
- Farhan, W., & Razmak, J., Demers, S., Laflamme, S. (2019). E-learning systems versus instructional communication tools: Developing and testing a new e-learning user interface from the perspectives of teachers and students. Technology in Society, 59, 101192.
- Razmak, J., Bélanger, C.H., & Farhan, W. (2018). Development of a techno-humanist model for e-health adoption of innovative technology. International journal of medical informatics, 120, 62-76.
- Razmak, J., Bélanger, C. H., & Farhan, W. (2018). Managing patients’ data with clinical decision support systems: a factual assessment. Journal of Decision Systems, 27(3), 123-145.
- Farhan, W., & Passi, K. (2016, January). E-learning User Interface for Visual and Hearing Impaired Students. In Proceedings of the International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government (EEE) (p. 10). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).
- Farhan, W. (2014). A comparative study of D2L's Performance with a purpose built E-learning user interface for visual-and hearing-Impaired students (Laurentian University of Sudbury).
- Decision Support Systems.(U)
- Business System Analysis & Applications.(U)
- Business Data Communication.(U)
- Fund. Of Innovation and Entrepreneurship.(U)
- Web Engineering.(U)
- Database Management Princples and Applications.(U)
- Knowledge Management.(U)
- Introduction to Programming Languages.(U)
E-learning systems versus instructional communication tools: Developing and testing a new e-learning user interface from the perspectives of teachers and students
Published in: Technology in Society
Sep 01, 2019
Focusing on Human E-learning Interaction (HEI), this interdisciplinary research integrates concepts from instructional communication and instructional technology and applies them to e-learning systems, focusing on academic stakeholders' roles and competencies. The purpose of this research is to propose and design an E-learning User Interface (ELUI) using web programming languages to support instructional communication in an online learning environment. The proposed interface, considering both students' and teachers' perspectives, identifies several new features that contribute to success in interactive e-learning systems in academic organizations. A sample of 102 students and 10 teachers selected from a university in Canada were asked to browse the ELUI proposed in this study and provide feedback. Using a mixed methods approach, this study employed both quantitative and qualitative methods of analysis to provide a more robust understanding of student and teacher perceptions of the ELUI. Students' attitudes toward use of the interface were analyzed using the Technology Acceptance Model, while teachers’ perceptions were analyzed through content analysis of semi-structured interviews. The results of regression analysis showed that perceived ease of use and perceived usefulness of ELUI are predictive of student attitude toward future use of the ELUI. The results of the interviews revealed that teachers believe the ELUI would be efficient, particularly with adequate training and support, though were unable to comment on the cost effectiveness of e-learning systems. The overall results suggest that academic decision-makers should adopt instructional communication features in e-learning systems.
Published in: Journal of Decision Systems
Sep 30, 2018
In assessing the benefits of using e-health systems, the main goal of this study is to evaluate the real use of the clinical decision support system (CDSS) between 2007 and 2014 in Canada’s healthcare sector. The quantitative method was based on data collected by the National Physician Survey in Canada. Results indicate that 63.8% of healthcare providers were using a CDSS at work in 2014 to help them in the decision-making process, a sixfold improvement since 2007. As for usage rate by sex, we found a statistically significant difference between men and women, with women from the Canadian physicians’ group reporting greater CDSS use than men. In all age groups, a higher percentage of younger physicians used a CDSS in their practice. A number of suggestions are put forth to improve technological infrastructure and reduce the gap among age groups, genders and specialties.
Published in: International Journal of Medical Informatics
May 17, 2018
Background and Purpose: After investing billions of dollars in an integrated Electronic Medical Records (physicians) and Personal Health Records (patients) system to allow both parties to manage and communicate through e-health innovative technologies, Canada is still making slow adoption progress. In an attempt to bridge the human and technological perspectives by developing and testing a holistic model, this study purports to predict patients’ behavioral intentions to use e-health applications. Methods: An interdisciplinary approach labelled as a techno-humanism model (THM) is testing twelve constructs identified from the technological, sociological, psychological, and organizational research literature and deemed to have a significant effect upon and positive relationship with patients’ e-health applications adoption. Subjects were Canadians recruited in a mall-intercept mode from a region representing a demographically diverse population, including rural and urban residents. The SmartPLS measurement tool was used to evaluate the reliability and validity of study constructs. The twelve constructs were separately tested with quantitative data such as factor analysis, single, multiple, and hierarchical multiple regression. Results: The hierarchical multiple regression analysis process led us to formulate four models, each hinged on a combination of interdisciplinary variables. Model 1 consisted of the technological predictors and explained 62.3% (p < .001) of variance in the behavioral intention to use e-health. Model 2 added the sociological predictors to the equation and explained 72.3% (p < .001) of variance. Model 3 added the psychological predictors to Model 2 and explained 72.8% (p < .001). Finally, Model 4 included all twelve predictors and explained 73% (p < .001) of variance in the behavioral intention to use e-health applications. Conclusions: One of the greatest barriers to applying e-health records in Canada resides in the lack of coordination among stakeholders. The present study implies that healthcare policy makers must consider the twelve variables with their findings and implications as a whole. The techno-humanist model (THM) we are proposing is a more holistic and continuous approach. It pushes back to a breakdown of the various technological, sociological, psychological, and managerial factors and stakeholders that are at the root cause of behavioral intentions to use e-health, as opposed to merely observing behavioral outcomes at the end of the “assembly line”. Active participation and coordination of all stakeholders is a key feature.