In the Spotlight - Interview with Dr.  Mohamed Benhima

In the Spotlight - Interview with Dr. Mohamed Benhima

Sumalatha G
Sumalatha G

Welcome to the latest edition of "In the Spotlight." This interview series is dedicated to bringing forth conversations with prominent researchers, offering a deep dive into their significant contributions, pivotal research, and visions for the future of their respective domains.

Today, we have the privilege of conversing with Dr. Mohamed Benhima, a leading researcher at Mohammed V University in Rabat, Morocco. Dr. Benhima's expertise predominantly lies in higher education quality assurance, with an emphasis on English language education. His commendable research articles, featured in peer-reviewed and Scopus-indexed journals, spans a range of topics — from motivation and learning strategies to the evolving perspectives on distance education. In compliance with the academic pursuits, Dr. Benhima has adeptly leveraged digital platforms, posting tutorials and academic content on his YouTube channel that garners millions of views annually.

Without further ado, let's see what this interview unfolds about Dr. Benhima's research journey, whose insights promise to be both illuminating and instructive for scholars and researchers in higher education and beyond.

Q: What are your current areas of specialization?

I specialize in research in higher education with a focus on data analysis, visualization, and interpretation of survey findings. Lately, data has become the oil of the century. My work offers novel insights to validate existing hypotheses, address research questions, and achieve research objectives. These insights are pivotal in addressing knowledge gaps within higher education and English language research domains. Given the importance of data in today's digital era, I emphasize the significance of technical proficiency and critical thinking in AI tools, including Excel, Python, R, and SPSS.

Q: What inspired you to become a researcher in the quantitative paradigm?

My journey into quantitative research began during my bachelor's program when my supervisor introduced me to his PhD dissertation, which was rooted in quantitative methodology. This exposure ignited my interest in the field. This quantitative approach was gradually enhanced in the master, PhD programs and later during my research experience at Sidi Mohamed Ben Abdellah University where I further adopted the mixed method approach by blending both qualitative data for exploration with quantitative data for confirmation. Courses on descriptive and inferential statistics have helped me get acquainted with the technical concepts including measures of central tendencies (mean, median, and mode), measures of dispersion (variance and standard deviation) and parametric/non-parametric inferential statistics of null and alternate hypothesis testing, such as T-Test, ANOVA, Correlation and Regression. Embracing the fact that reality can often be best understood through quantifiable data, I specialized in quantitative research. As an induced effect, this quantitative mindset even influenced my personal life, where I began measuring productivity time, calories for weight management, and income against expenses to ensure a quality life. So, this is how my quantitative research journey started.

Q: What research topics are you currently working on?

I'm primarily working on structural equation modeling within higher education, leveraging advanced tools like Python, RStudio, and SmartPLS 4. My research framework heavily relies on AI tools, notably SciSpace (Typeset), which streamlines the process of research discovery and reading. The tool's capability to suggest research paper-relevant queries and compile summaries of top papers, especially those cited in APA format — a widely accepted style for journal publications—is particularly valuable. Currently, I'm heading seminars on Technology Acceptance Models (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Here, students engage in crafting, validating, or utilizing Likert scales to quantify both latent and manifest constructs, aimed at theory validation. Our emphasis also extends to the unique challenges in the Moroccan context, where certain technologies, such as Metaverse and region-specific AI tools, remain less accessible.

Q: What advice can you give to novice researchers?

Continuous learning and development are pivotal in research. It's imperative for researchers to enhance their skills, especially in the arena of data and analysis. While there's a wealth of free educational resources available, distractions from social media can deter researchers from engaging in online courses, reading, and writing. Hence, researchers should develop self-control, time-management skills and other soft skills for increased productivity and innovation in their fields. Researchers should also channel their energies into a singular area of expertise to make a meaningful impact, rather than spreading themselves thinly across multiple domains. For researchers, their skills are the cornerstone and real investments in the research journey.

And that's a wrap!

We would like to thank Dr. Mohamed Benhima for partaking in this interview. If you're thinking about diving into the data analysis domain, we hope this conversation gave you that tiny dose of inspiration. And remember, if you're looking for some guidance with quantitative research, Dr. Benhima is your go-to person.