Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology
Open accessAbstract
The university’s computer laboratory is currently one of the most challenging aspects when imparting practical tasks with regards to the education technology (ET) enhancement. This study intends to observe the issues confronted by students while performing tasks in the laboratory in different educational modes. The online survey is conducted using quantitative and qualitative research instruments to evaluate the students’ perspectives. This exploratory work has emphasized the practical issues such as an insufficient time constraint, and instruments, geographical needs, financial concerns, and unavailability of subject specialists to cater for relevant issues about a particular course. The sample size was (N= 161) drawn from a stratified sampling method for analysis of four strata. This research addresses these problems in the laboratory with an aim to improve the student’s practical skills as well as their investigation-based learning. It is needed for practical based courses, through experimentation with the help of artificial intelligence (AI) paradigms. The design science methodology is adopted, it presents the conception of an Intelligent Virtual Laboratory (IVL) based on pedagogical agent-based cognitive architecture (PACA). This IVL provides the level of excellence of laboratory needs by enhancing the ET which students can efficiently perform practical tasks online at anywhere. The results showed that IVL has a significant model for enhancing the learning to students and recommendations for further research implementation.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Cites
Guest, G., MacQueen, K., & Namey, E. (2012) · doi:10.4135/9781483384436 · Cited by 7,924 · see citing works
Virtual laboratories for education in science, technology, and engineering: A review
Potkonjak, V., Gardner, M., Callaghan, V., Mattila, P., Gütl, C., Petrović, V. M., & Jovanovic, K. M. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.02.002 · Cited by 1,020 · cited 2× · see citing works
“Multiple virtual laboratories have been existing through different approaches, and it is motivated that the virtual laboratory (VL) is one of the demanding aspects of spreading learning resources and practical activities of the online education system (Potkonjak et al., 2016; Stark, Bistak, Kozak, & Kucera, 2017).”
BackgroundCognitive architectures: Research issues and challenges
Langley, P., Laird, J. E., & Rogers, S. (2009) · Cognitive Systems Research · doi:10.1016/j.cogsys.2006.07.004 · Cited by 728 · see citing works
Design Science Research Methods and Patterns
Vaishnavi, V. K. (2007) · Auerbach Publications eBooks · doi:10.1201/9781420059335 · Cited by 485 · see citing works
Nye, B. D. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0028-6 · Cited by 259 · cited 2× · see citing works
“The virtual laboratory can resolve the practical activities in a virtual environment through the adaptive pedagogical methods and students can be more engaged when they build they’re own analytical and knowledge skills about practical concepts and demonstrate it in an adaptive learning system (Nye, 2015; Ozana & Docek…”
BackgroundHuman Symbol Manipulation Within an Integrated Cognitive Architecture
Anderson, J. R. (2005) · Cognitive Science · doi:10.1207/s15516709cog0000_22 · Cited by 253 · cited 1× · see citing works
“CA supported the active agent’s behaviour from the accessibility of knowledge acquisition such as SOAR (Lehman, Laird, & Rosenbloom, 2006), ACT R (Anderson, 2005), BICA (Samsonovich, 2012), IDA, and LIDA (Franklin & Ferkin, 2006) architecture.”
MethodA Gentle Introduction to Soar, an Architecture for Human Cognition.
Lehman, J. F., Laird, J. E., & Rosenbloom, P. S. (1996) · Cited by 168 · see citing works
Susan Bull, A., & Kay, J. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0090-8 · Cited by 165 · cited 1× · see citing works
“Assessment of learners has been grounded on different learning models, such as a SMILI framework, which provided the comparison between open learning models (OLM) (Bull & Kay, 2016).”
MethodHow valuable is information and communication technology? A study of emerging economy enterprises
Luo, Y., & Bu, J. (2015) · Journal of World Business · doi:10.1016/j.jwb.2015.06.001 · Cited by 162 · see citing works
Cognitive Architectures: Where do we go from here?
Duch, W., Oentaryo, R. J., & Pasquier, M. (2008) · Artificial General Intelligence · Cited by 151 · see citing works
Niels Pinkwart, C. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0099-7 · Cited by 138 · cited 2× · see citing works
“Frameworks of VL have been ramped up through artificial intelligence techniques as autonomous and adaptive systems in (Nye, 2016; Pinkwart, 2016; Porayska- Pomsta, 2016; Zhuoyuan, Lingong, Ping, & Yigang, 2017).”
BackgroundMethodOn a roadmap for the BICA Challenge
Samsonovich, A. V. (2012) · Biologically Inspired Cognitive Architectures · doi:10.1016/j.bica.2012.05.002 · Cited by 92 · cited 2× · see citing works
“Samsonovich presented the cognitive constructor which was founded on a GMU BICA cognitive architecture for modelling self-regulated problem-solving skills enables students to develop self-regulation skills for mathematical problems (Samsonovich, Kitsantas, O’Brien, & De Jong, 2015).”
MethodLab4CE: a Remote Laboratory for Computer Education
Broisin, J., Venant, R., & Vidal, P. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0079-3 · Cited by 63 · cited 1× · see citing works
“The practical activities in online education in different domains of scientific discipline and applied science have investigated, to be offered to distance learning and blended learning students through a distinct prospect of the framework or techniques (Broisin et al., 2015).”
BackgroundAI as a Methodology for Supporting Educational Praxis and Teacher Metacognition
Porayska‐Pomsta, K. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0101-4 · Cited by 51 · see citing works
Diwakar, S., Kumar, D. P., Radhamani, R., Sasidharakurup, H., Nizar, N., Achuthan, K., Nedungadi, P., Raghu Raman, R., & Nair, B. G. (2016) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v12i03.5391 · Cited by 49 · cited 1× · see citing works
“It has focused on the blended education through a virtual and remote lab for undergraduate and graduate teaching in the different field of biotechnology and biomedical engineering (Diwakar et al., 2016).”
BackgroundSamsonovich, A. V., Jong, K. A. D., Kitsantas, A., Peters‐Burton, E. E., Dabbagh, N. H., & Kalbfleisch, M. L. (2008) · Artificial General Intelligence · Cited by 24 · see citing works
An Ontology for Comparative Cognition: A Functional Approach
Franklin, S., & Ferkin, M. H. (2006) · Comparative Cognition & Behavior Reviews · doi:10.3819/ccbr.2008.10003 · Cited by 21 · cited 1× · see citing works
“CA supported the active agent’s behaviour from the accessibility of knowledge acquisition such as SOAR (Lehman, Laird, & Rosenbloom, 2006), ACT R (Anderson, 2005), BICA (Samsonovich, 2012), IDA, and LIDA (Franklin & Ferkin, 2006) architecture.”
MethodITS, The End of the World as We Know It: Transitioning AIED into a Service-Oriented Ecosystem
Nye, B. D. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0098-8 · Cited by 20 · cited 1× · see citing works
“Frameworks of VL have been ramped up through artificial intelligence techniques as autonomous and adaptive systems in (Nye, 2016; Pinkwart, 2016; Porayska- Pomsta, 2016; Zhuoyuan, Lingong, Ping, & Yigang, 2017).”
MethodVirtual laboratory based on Node.js technology
Stark, E., Bisták, P., Kozák, Š., & Kučera, E. (2017) · International Conference on Process Control · doi:10.1109/pc.2017.7976245 · Cited by 20 · see citing works
Gilbert, S. B., Blessing, S. B., & Guo, E. (2015) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-015-0045-0 · Cited by 17 · see citing works
The concept of virtual laboratory and PIL modeling with REX control system
Ožana, Š., & Dočekal, T. (2017) · International Conference on Process Control · doi:10.1109/pc.2017.7976196 · Cited by 10 · see citing works
Non-intrusive assessment of learners’ prior knowledge in dialogue-based intelligent tutoring systems
Rus, V., & Stefanescu, D. C. (2016) · Smart Learning Environments · doi:10.1186/s40561-016-0025-3 · Cited by 9 · cited 1× · see citing works
“Deep Tutor projects are operating on a macro and micro adaptations by proposing the framework (Rus & Stef, 2011).”
Cognitive Processes in Preparation for Problem Solving
Samsonovich, A. V., Kitsantas, A., O’Brien, E. J., & Jong, K. A. D. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.12.218 · Cited by 3 · see citing works
Virtual laboratory technology for educational electromagnetics
Wang, Z., Li, L., Ping, Y., & Wang, Y. (2016) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2016.7831964 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 7
- Munawar, S., Khalil Toor, S., Aslam, M., Martinez Enriquez, A., & Hamid, M. (2017). Pedagogical Agent-based Cognitive Architecture for an Intelligent Virtual Laboratory Cloud-based HCI E-learning Environment. International Conference on Open and Innovative Education (ICOIE 2017).
- Munawar, S., Toor, S. K., Aslam, M., & Hamid, M. (2018). Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology. Eurasia Journal of Mathematics, Science and Technology Education, 14(5), 1645-1662. https://doi.org/10.29333/ejmste/85036
- Munawar S, Toor SK, Aslam M, Hamid M. Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology. EURASIA J Math Sci Tech Ed. 2018;14(5):1645-62. https://doi.org/10.29333/ejmste/85036
- Munawar S, Toor SK, Aslam M, Hamid M. Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology. EURASIA J Math Sci Tech Ed. 2018;14(5), 1645-1662. https://doi.org/10.29333/ejmste/85036
- Munawar, Saima, Saba Khalil Toor, Muhammad Aslam, and Muhammad Hamid. "Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology". Eurasia Journal of Mathematics, Science and Technology Education 2018 14 no. 5 (2018): 1645-1662. https://doi.org/10.29333/ejmste/85036
- Munawar, S., Toor, S. K., Aslam, M., and Hamid, M. (2018). Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology. Eurasia Journal of Mathematics, Science and Technology Education, 14(5), pp. 1645-1662. https://doi.org/10.29333/ejmste/85036
- Munawar, Saima et al. "Move to Smart Learning Environment: Exploratory Research of Challenges in Computer Laboratory and Design Intelligent Virtual Laboratory for eLearning Technology". Eurasia Journal of Mathematics, Science and Technology Education, vol. 14, no. 5, 2018, pp. 1645-1662. https://doi.org/10.29333/ejmste/85036
Cited by
Sorted by citations
A Review of Artificial Intelligence (AI) in Education from 2010 to 2020
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021) · Complexity · doi:10.1155/2021/8812542 · Cited by 1,364 · see citing works
“For example, with the help of pedagogical agent-based cognitive architecture, the intelligent virtual laboratory was developed to give appropriate feedback to students who encounter difficulties in the laboratory [35].”
BackgroundChiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100118 · Cited by 1,181 · see citing works
AI technologies for education: Recent research & future directions
Zhang, K., & Aslan, A. B. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100025 · Cited by 923 · see citing works
Future research recommendations for transforming higher education with generative AI
Chiu, T. K. F. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100197 · Cited by 511 · see citing works
Fahyuni, E. F., Wasis, W., Bandono, A., & Arifin, M. B. U. B. (2020) · Jurnal Pendidikan IPA Indonesia · doi:10.15294/jpii.v9i2.23209 · Cited by 77 · see citing works
“Integration learning with religion, science, and skills (Munawar et al., 2018).”
BackgroundUnderstanding socio-technological challenges of smart classrooms using a systematic review
Alfoudari, A. M., DURUGBO, C. M., & Aldhmour, F. M. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104282 · Cited by 109 · see citing works
Exploring quality attributes of smart classrooms from the perspectives of academics
Alfoudari, A. M., DURUGBO, C. M., & Aldhmour, F. M. (2023) · Education and Information Technologies · doi:10.1007/s10639-022-11452-3 · Cited by 31 · see citing works
“Challenges also arise in personalizing the learning environment to promote learning attitudes and motivation (Munawar et al., 2018; Tlili et al., 2019; Aguilar et al., 2017).”
BackgroundPROMISES AND PERILS OF AI USE ON THE TERTIARY EDUCATIONAL LEVEL
Lukianets, H., & Lukianets, T. (2023) · ГРААЛЬ НАУКИ · doi:10.36074/grail-of-science.17.03.2023.053 · Cited by 22 · see citing works
Hernández-León, N., & Conde, M. J. R. (2024) · Revista de Educación a Distancia (RED) · doi:10.6018/red.594651 · Cited by 21 · see citing works
“También son relevantes los IVL o Laboratorios Virtuales Inteligentes, donde el alumno puede desarrollar tareas prácticas online con un nivel de excelencia, mejorando el aprendizaje de los estudiantes (Curiel-Ramírez et al., 2022; Munawar et al., 2018).”
BackgroundInfluentialCOGNITIVE AND METACOGNITIVE SKILLS OF STUDENTS IN THE CONTEXT OF SMART-EDUCATION
Bataeva, E. V. (2019) · The Education and science journal · doi:10.17853/1994-5639-2019-4-36-59 · Cited by 20 · see citing works
“Хамид определяют роль компьютерных лабораторий университетов в технологическом обеспечении смарт-образования [15].”
An intelligent decision support system for effective handling of IT projects
Hamid, M., Zeshan, F., Ahmad, A., Munawar, S., Aı̈meur, E., Ahmed, S., Elsoud, M. A. A., & Yousif, M. J. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-179550 · Cited by 19 · see citing works
“Some other projects were also explored related to recommender and multi-agent systems for better prediction [26].”
Self-citationAI in Education and Learning: Perspectives on the Education Ecosystem
Niemi, H. (2024) · Springer eBooks · doi:10.1007/978-3-031-61187-2_11 · Cited by 22 · see citing works
Improving Learning Abilities Using AI-Based Education Systems
Kumar, A., Singh, D., & Vohra, R. (2023) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-0378-8.ch006 · Cited by 16 · see citing works
WITHDRAWN: Design and implementation of intelligent virtual laboratory using RASA framework
Deepika, N. M., Bala, M. M., & Kumar, R. (2021) · Materials Today Proceedings · doi:10.1016/j.matpr.2021.01.226 · Cited by 15 · see citing works
RetractedStudents’ Attitudes towards AI in Teaching and Learning
Dobrovská, D., Vaněček, D., & Yorulmaz, Y. İ. (2024) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v14i8.52731 · Cited by 19 · see citing works
A Systematic Literature Review Enhanced Felder Silverman Learning Style Models (FSLSM)
Supangat, S., & Saringat, M. Z. (2022) · International Conference on Informatics and Computing (ICIC) · doi:10.1109/icic56845.2022.10006958 · Cited by 11 · see citing works
“…with MCD[15][51]. educational technology acceptance and satisfaction model[15], five grade rating[29]. quantitative method with statistical tools[40][41][43][44] [46][47][48][49][55], image processing[42], MCDM with Fuzzy analytical hierarchy process[50], design-based[52], and K-means…”
MethodInfluentialPersepsi Mahasiswa terhadap Penggunaan Virtual Laboratory dalam Pembelajaran Biologi Molekuler
Suryanti, E., Fitriani, A., Redjeki, S., & Riandi, R. (2019) · Journal of Natural Science and Integration · doi:10.24014/jnsi.v2i2.7884 · Cited by 10 · see citing works
Artificial intelligence in biology and learning biology: A literature review
Aripin, I., Gaffar, A. A., Jabar, M. B. A., & Yulianti, D. (2024) · Journal of Mangifera Edu · doi:10.31943/mangiferaedu.v8i2.185 · Cited by 9 · see citing works
“Virtual laboratory Teaching media Virtual Laboratory (Munawar et al., 2018) Figure 3 shows that AI systems for education generally consist of teaching content, data, and intelligent algorithms, which can be divided into two parts: system models (including learner models, teaching models, and…”
BackgroundUse of Artificial Intelligence in Education: A Systematic Review
Bandara, W. M. H. K., & Senanayaka, S. G. M. S. D. (2024) · International Research Conference on Smart Computing and Systems Engineering (SCSE) · doi:10.1109/scse61872.2024.10550527 · Cited by 8 · see citing works
“Munawar et al. [18] innovatively devised a program of intelligent laboratory in virtual method to meet the needs of students by assigning tasks tailored to their proficiency level.”
MethodHow University students in Bangladesh engage with ChatGPT: A qualitative study
Hasib, M., & Islam, M. S. (2025) · PLoS ONE · doi:10.1371/journal.pone.0333089 · Cited by 14 · see citing works
A Review of the Application of Artificial Intelligence in the Virtual Learning Environment
Wei, X., & Jia, H. (2021) · International Conference of Educational Innovation through Technology (EITT) · doi:10.1109/eitt53287.2021.00024 · Cited by 8 · see citing works
Desriana, D., Khaldun, I., Maulana, I., Habibati, H., & Ismayani, A. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1460/1/012092 · Cited by 8 · see citing works
Utilization of Artificial Intelligence in Education: A Perspective on Learning Strategies
Yalçınalp, S., Türkoğlu, H., Koç, S. E., & Ersoy, H. (2024) · Artificial intelligence · doi:10.5772/intechopen.1005086 · Cited by 12 · see citing works
A Conceptual Multi-Dimensional Model for Smart Learning Environments
Maulidiya, D., Santoso, H. B., & Hasibuan, Z. A. (2019) · International Conference on Advanced Computer Science and Information Systems · doi:10.1109/icacsis47736.2019.8979679 · Cited by 7 · see citing works
“Architecture [3], [4], [10]–[12], [16], [18], [21], [24], [25]”
BackgroundMethodResearch methodology for computer science
Nasution, M. K. M., Elveny, M., & Syah, R. B. Y. (2023) · AIP conference proceedings · doi:10.1063/5.0134511 · Cited by 5 · see citing works
Immersive Learning at Scale: Exploring the Feasibility of VR in Education
Soltani, N., & Rostami, A. (2025) · ACM International Conference on Interactive Media Experiences · doi:10.1145/3706370.3727859 · Cited by 5 · see citing works
“It echoes earlier challenges, such as sharing lab computers among large student groups [10, 23], the rise of personal mobile app accounts [2], and even shared family access to digital devices [13, 24].”
Yapay Zekanın Eğitimdeki Etkisinin İncelenmesi Üzerine Bir Alan Araştırması
Korkmaz, M. S., & Polat, S. (2023) · International Conference on Recent and Innovative Results in Engineering and Technology (ICRIRET) · doi:10.59287/icriret.1371 · Cited by 5 · see citing works
Instructional design of smart technology use in teacher digital educational environment
Sarzhanova, G. B., Bobesh, R. S., Смагулова, Г. Ж., Türkel, A., & Serikbayeva, N. B. (2023) · The Education and science journal · doi:10.17853/1994-5639-2023-9-12-45 · Cited by 5 · see citing works
Obsolescencia del conocimiento vs formación para el desarrollo sostenible
Soledad, M. (2021) · Texto Livre Linguagem e Tecnologia · doi:10.35699/1983-3652.2021.33840 · Cited by 5 · see citing works
Understanding how to assess the impact of Artificial Intelligence on learning: a systematic review
Cloux, M., Monticolo, D., & Bary, R. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2468986 · Cited by 4 · see citing works
Okolo, C. T., & Lin, H. (2024) · ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) · doi:10.1145/3689904.3694707 · Cited by 3 · see citing works
Kaur, H., Reddy, C. K. K., Reddy, D., & Hanafiah, M. M. (2025) · Springer eBooks · doi:10.1007/978-981-96-2355-6_13 · Cited by 5 · see citing works
Baltaci, K., Herrmann, M., & Turkmen, A. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--47644 · Cited by 3 · see citing works
“Additionally, AI-powered virtual laboratories offer greater accessibility and cost-effectiveness, allowing students to access a wide range of resources anytime and anywhere [9].”
Virtual Laboratory as a Tool to Empower IT Students
Ялова, К. М., Babenko, M., Babenko, Y., Polyakova, N., & Anna, Z. (2025) · Springer eBooks · doi:10.1007/978-3-031-82243-8_15 · Cited by 3 · see citing works
A Design of Smart Beaker Structure and Interaction Paradigm Based on Multimodal Fusion Understanding
Dong, D., Feng, Z., Yuan, J. H., Meng, X., Meng, J., & Kong, D. (2020) · IEEE Access · doi:10.1109/access.2020.3025229 · Cited by 2 · see citing works
“With the help of an artificial intelligence paradigm, Munawar et al. [14] proposed an intelligent virtual laboratory using a pedagogical agent-based cognitive architecture.”
MethodEybers, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40113-8_38 · Cited by 2 · see citing works
Design of a new kind of chemical experiment container with virtual reality fusion
Yang, L., Feng, Z., & Meng, J. (2023) · Virtual Reality & Intelligent Hardware · doi:10.1016/j.vrih.2022.07.008 · Cited by 2 · see citing works
The Effect of Artificial Intelligence Over the Educational System (School and University)
Omidi, S., & Omidi, A. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-0993-3.ch008 · Cited by 2 · see citing works
Niu, S. J., Niemi, H., Li, X., Luo, J., & Lu, Y. (2026) · Springer eBooks · doi:10.1007/978-3-032-12174-5_18 · Cited by 1 · see citing works
Design computer laboratory friendly for disabilities
Sukriman, S., Sumarto, S., & Abdullah, A. G. (2020) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/830/4/042074 · Cited by 1 · see citing works
“Besides the design and development of the environment must pay attention to the needs of people with disabilities, so far the design and development of the environment does not pay attention to the needs of people with disabilities [4].”
BackgroundLearning Problems of Prospective Teachers in Lectures Modern Physics During the Covid-19 Pandemic
Juandi, T., Kaniawati, I., Samsudin, A., Verawati, N. N. S. P., & Zahara, L. (2024) · KnE Social Sciences · doi:10.18502/kss.v9i13.16064 · Cited by 1 · see citing works
“Practicum can be carried out, even though learning is carried out remotely [5, 47].”
BackgroundÁvila, F. L. C., Vélez, K. N. G., Guerrero, B. R. C., Agurto, L. G. B., Guaraca, A. M. S., & González, L. J. L. (2024) · Ciencia Latina Revista Científica Multidisciplinar · doi:10.37811/cl_rcm.v8i3.11536 · Cited by 1 · see citing works
Investigation on Innovative Models of Computer Laboratories Based on Cloud Computing
Zhang, Q., & Guo, H.-Y. (2023) · Procedia Computer Science · doi:10.1016/j.procs.2023.11.044 · Cited by 1 · see citing works
The differences of e-learning web course based on mathematics learning achievement at grade XI
Arigiyati, T. A., Lilhawa, R. K., & Taufiq, I. (2023) · Jurnal Math Educator Nusantara Wahana Publikasi Karya Tulis Ilmiah di Bidang Pendidikan Matematika · doi:10.29407/jmen.v9i1.18863
“The COVID-19 outbreak has prompted testing of distance education that has almost never been conducted simultaneously before (Munawar et al., 2018).”
BackgroundChattitude in Education: Chatbot Expertise for Educational System
Shree, K. S. K., Sangeetha, P. R., Upadhyay, S., & Devi, S. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-82386-2_22
N-Sand Table: A Multi-user Interactive Virtual Sand Table Based on NeRF Technology
Zhang, X., Yu, J., Gong, C., Huang, D., Sun, Y., & Zhou, X. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-2684-7_3
Gu, H. (2025) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2025-0756
Li, Z., & Deng, W. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1473555
Introduction to AI-Powered Educational Games and Simulations
Munawar, S., Naveed, N., & Munawar, M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0035-1.ch001
Self-citationBridging Gamification and Assessment
Khawar, K., Munawar, S., & Naveed, N. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0035-1.ch003
Self-citationПЕРЕВАГИ ТА НЕДОЛІКИ ВИКОРИСТАННЯ ШТУЧНОГО ІНТЕЛЕКТУ В ОСВІТІ
Блажко, В. О. (2025) · Актуальні питання у сучасній науці · doi:10.52058/2786-6300-2025-6(36)-868-881
Agent-Based Approaches Towards Smart Higher Education: A Preliminary Review
Kasaii, M. S., Rossetti, R. J. F., & Campos, P. (2025) · IEEE International Smart Cities Conference (ISC2) · doi:10.1109/isc266238.2025.11293344
“The Enhanced Learning Outcomes category ranked second with 14 articles documenting practical examples [12], [16], [18], [20], [22], [24], [25], [27], [36], [37], [40]–[43].”
Balushi, A. M. A. A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4982-4.ch009
Jaleel, S., & George, M. (2026) · International Journal of Latest Technology in Engineering Management & Applied Science · doi:10.51583/ijltemas.2026.150500155
- Authors
- Munawar, S., Toor, S. K., Aslam, M., & Hamid, M.
- Affiliations
- National College of Business Administration and Economics (PK)
- Forman Christian College (PK)
- University of Engineering and Technology Lahore (PK)
- Corresponding author
- Munawar, Saima
- Venue
- EURASIA Journal of Mathematics, Science and Technology Education
- Publisher
- Modestum Publishing Ltd
- Published
- 2018-02-04
- Volume
- 14
- Issue
- 5
- ISSN
- 1305-8215 (ISSN-L)
- 1305-8223
- OpenAlex
- W2786465123
- Cited by
- 54
- References
- 24
- Citations by year
- 2026: 3 · 2025: 13 · 2024: 11 · 2023: 11 · 2022: 2 · 2021: 6 · 2020: 4 · 2019: 4
- FWCI
- 2.65
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Eurasia Journal of Mathematics Science and Technology Education (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Media Technology › Experimental Learning in Engineering
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Keywords
- online learning, educational agents, cognitive architecture, practical skills, student perceptions, artificial intelligence in education, design science methodology
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
