VIRAL: The Effectiveness of Virtual Lab Teaching in Developing Higher Order Thinking Skills
Abstract
Virtual Innovation & Research Acceleration Lab (VIRAL) is an ongoing teaching pedagogy project between SRM Institute of Science & Technology, Ramapuram Campus, Chennai and MIT Square, London. In the higher education sector, the year 2020 posed new obstacles. All three waves of the COVID-19 pandemic necessitated a shift in the mentality of educators, teachers, and students from all over the world. The concerns and obstacles associated with higher educational institutions’ rapid and abrupt transition from face-to-face learning to technology-assisted virtual learning. This study examines the effectiveness of Virtual Innovation & Research Acceleration Labs (VIRAL) teaching in developing Higher Order Thinking Skills (HOTS) among engineering students. The researchers employed a Quasi-Experimental method. The sample consisted of 98 Engineering students who have regular laboratory classes as part of their curriculum. A group consisting of 49 students was selected as a control group and another group was selected as an experimental group randomly. The result of the study indicates that the experimental group has a greater mean of higher-order thinking skills than the control group. Thus it is concluded that the virtual lab teaching method for research and innovation has a significant positive effect in enhancing higher thinking skills in engineering. The study also has implications for facilitation in the higher order of inquiry processes and improvement of slow learners.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previous studies have highlighted the importance of using virtual laboratories as a tool in learning activities and laboratory work.
“For instance, previous studies have highlighted the importance of using virtual laboratories as a tool in learning activities and laboratory work (Abdulrahman Nami Alshaikh 2022; Raja et al. 2021).”
From Incorporating Computational Thinking Into Virtual Laboratories to Enhance Learning Motivation, Engagement, and Higher‐Order Thinking Skills (2025) · cites this paper as Raja et al. 2021
Cited by
Sorted by citations
Wu, T., Sarwono, E., & Huang, Y. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70017 · Cited by 9 · see citing works
- Authors
- Raja, K., Duela, J. S., Duraipandian, K., Rajan, S., & Sathiyanarayanan, M.
- Affiliations
- SRM Institute of Science and Technology (IN)
- MIT Square,Research & Innovation,India & UK
- Venue
- 2021 1st Conference on Online Teaching for Mobile Education (OT4ME)
- Publisher
- IEEE
- Published
- 2021-11-22
- Pages
- 116-117
- OpenAlex
- W4200214447
- Cited by
- 1
- References
- 0
- Citations by year
- 2025: 1
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Conference on Online Teaching for Mobile Education (OT4ME) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Media Technology › Experimental Learning in Engineering
- Social Sciences › Education › Education and Critical Thinking Development
- Social Sciences › Education › Technology-Enhanced Education Studies
- Keywords
- virtual laboratory, higher-order thinking skills, engineering education, laboratory teaching, COVID-19 pandemic, inquiry-based learning, slow learners
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review