Abstract
This paper examines the shift to remote and distance learning in experiential education for electronic, electrical, and computer engineering courses in Ireland during the COVID-19 pandemic. As higher education institutions were required to redesign laboratory sessions for remote delivery, the study identifies and categorises the approaches adopted across engineering faculties at Irish third-level institutions. Data were collected from 33 respondents representing 12 higher education institutions, exploring the implementation and perceived effectiveness of different remote laboratory methods. The findings identify five delivery models: learning simulations, remote lab kits, electronic lab notebooks/e-books, portfolios/formative assessment, and Problem-Based Learning (PBL). Institutional responses largely converged on two approaches—learning simulations and take-home hardware kits—reflecting pragmatic solutions under pandemic constraints. Remote laboratory kits accounted for approximately 37% of responses, while learning simulations represented 26% of reported implementations. Respondents consistently reported a trade-off between scalability and pedagogical value. Learning simulations were preferred for larger cohorts and limited resources, whereas take-home hardware kits were considered more effective for developing practical skills but required greater implementation effort. The study highlights how emergency teaching conditions influenced decision-making, leading to solutions that balanced continuity of experiential learning with operational feasibility rather than optimised instructional design.
Introduction
With the arrival of the Covid-19 virus on the world stage and the subsequent requirement to transition third-level teaching and associated experiential education to virtual and online environments, higher education systems worldwide were compelled to adapt rapidly. Lecturers in many disciplines found themselves delivering content, assessing progress, and grading student work entirely remotely, often with limited preparation time or institutional precedent (Wang et al., 2020). In engineering and other practice-oriented fields, similar challenges were documented internationally, with institutions adopting a range of emergency measures including remote laboratories, simulation-driven instruction, virtual experiments, and alternative assessment strategies across Europe, the Americas and Asia (Araujo et al., 2009; Dastfan, 2007; Dickerson and Clark, 2018; Viegas et al., 2018).
In disciplines such as electronic, electrical, and computer engineering, the disruption was particularly acute. Experiential education sessions that traditionally relied on face-to-face laboratory environments — where affective and psychomotor skills are developed alongside cognitive learning — could no longer be delivered in their established form (Feisel and Rosa, 2005). This raised a fundamental question faced by engineering educators internationally: how can essential skills such as circuit design, measurement, debugging, and evaluation be effectively developed when students are physically separated from laboratory infrastructure?
This paper presents an analysis of data gathered from a survey administered to a cross-section of electronic, electrical, and computer engineering lecturers and departmental representatives across higher education institutions (HEIs) in Ireland to examine how this challenge was addressed in practice. Ireland provides a distinctive and valuable context for such a study. The Irish higher education sector is relatively small, nationally regulated, and aligned under common quality assurance and professional accreditation frameworks. At the same time, it comprises a diverse mix of universities and technological universities serving varied student cohorts. This structure enables a coherent national comparison of pedagogical responses implemented under shared policy, regulatory, and temporal constraints.
The survey gathered information on the alternative delivery methods adopted for experiential laboratory sessions during the pandemic, capturing both implementation details and lecturers’ perceptions of effectiveness, feasibility, and limitations. Drawing directly on lecturer and facilitator perspectives, the survey identified five broad categories of remote or virtual laboratory approaches employed across Irish engineering programmes: learning simulations; take-home or remote laboratory hardware kits; electronic laboratory notebooks or e-books; portfolio-based and formative assessment approaches; and problem-based learning (PBL). These methods span a spectrum from technology-centric substitutes for physical laboratories to assessment- and pedagogy-driven reconfigurations of experiential learning.
While existing literature documents individual implementations of these approaches in specific national or institutional settings — such as simulation-based laboratories in the United States (Dickerson and Clark, 2018), web-based tools in Iran (Dastfan, 2007), and remote laboratories in Portugal and Brazil (Araujo et al., 2009; Viegas et al., 2018) — most prior studies focus on isolated case studies or single technologies. What remains less well understood is how these diverse approaches compare when deployed concurrently across a single national higher education system during a period of crisis, and how educators evaluate their relative strengths and limitations when making pragmatic teaching decisions under shared constraints.
By surveying the Irish HEI sector, this paper provides a high-resolution snapshot of a coordinated national response to the disruption of experiential engineering education. The study offers a comparative overview of five distinct delivery methodologies implemented under common institutional, policy, and accreditation conditions. Beyond the Irish context, the findings contribute transferable insights into pedagogical resilience in engineering education, highlighting how different remote laboratory strategies align with learning outcomes, resource constraints, and cohort characteristics when physical laboratory access is restricted.
The remainder of this paper is organised as follows. The next section presents a review of relevant academic literature on remote and distance learning approaches for experiential engineering education. The Methodology section describes the survey design and data collection process. Survey findings are then presented and analysed in the Results & Discussions section, followed by Conclusions and Practical Considerations, which summarise the key insights and implications for future engineering education practice.
Literature review
Experiential education foregrounds learning through direct experience, reflection, and iterative problem-solving. In electronic, electrical, and computer engineering, this approach has traditionally relied on face-to-face laboratory sessions where students develop not only conceptual understanding but also psychomotor skills, diagnostic reasoning, and professional intuition. The period of Emergency Remote Teaching (ERT) during the COVID-19 pandemic (2020–2022) dramatically accelerated experimentation with alternative laboratory delivery models. Five broad approaches have emerged in the literature as substitutes or complements to physical laboratories: learning simulations, remote and virtual laboratories (including take-home kits), electronic laboratory notebooks and interactive e-books, portfolio-based formative assessment, and problem-based learning (PBL). While each is well documented in isolation, comparative evidence regarding their relative strengths and weaknesses at scale remains limited.
Learning simulations
Learning simulations replicate laboratory environments through software-based tools that allow students to design circuits, execute experiments, and collect data without physical equipment. Pre-pandemic studies emphasised the conceptual benefits of simulation-centric pedagogy, particularly in microelectronics and analogue electronics education, where tools such as SPICE improved student comprehension of abstract models and reduced cognitive load associated with complex calculations (Dickerson and Clark, 2018; Zhang and Jie, 2018). However, a recurring limitation identified in the literature is the “idealisation problem”: simulations typically omit component tolerances, measurement noise, and hardware faults that are central to real-world engineering practice.
Post-2020 studies acknowledge that simulations were essential for continuity of teaching during lockdowns, offering scalability, low cost, and rapid deployment (Wijenayake et al., 2021). Nevertheless, concerns persist that heavy reliance on simulations can foster a situation where students become proficient in manipulating idealised systems yet struggle to transfer those skills to physical environments (Campbell et al., 2002). Thus, while simulations are effective for introducing theory and encouraging experimentation, the literature increasingly frames them as assisting as opposed to replacing hands-on laboratory work (Taher and Khan, 2015; Valencia De Almeida et al., 2022).
Remote and virtual laboratory implementations
Remote and virtual laboratories seek to reintroduce hardware interaction through either centralised facilities or distributed systems. Centralized remote labs — such as VISIR (Alves, 2023) — enable students to access professional-grade equipment via the internet and have demonstrated strong alignment with real-world instrumentation practices (Araujo et al., 2009; Viegas et al., 2018). However, these systems face well-documented challenges related to scalability, scheduling congestion, and institutional cost, issues that became more pronounced under pandemic-driven mass adoption (Jacob et al., 2025).
Take-home laboratory kits emerged as a prominent alternative during the pandemic, supported by advances in low-cost microcontrollers and compact instrumentation (Hill et al., 2021; Rossiter et al., 2019; Tran et al., 2019). The literature consistently reports increased student autonomy, flexibility, and engagement associated with home-based kits. Yet, these benefits are offset by limitations in experimental complexity, variability in student home environments, and substantial administrative burden related to distribution, maintenance, and technical support. Post-pandemic evaluations suggest that while students value the convenience of take-home kits, they continue to associate physical laboratories with richer peer learning and informal troubleshooting opportunities (Evstatiev et al., 2022).
Electronic laboratory notebooks and interactive E books
The shift to remote delivery accelerated the adoption of electronic laboratory notebooks (ELNs) and interactive e-books as replacements for paper-based documentation. Early studies found little difference in summative learning outcomes between digital and traditional materials (Almekhlafi, 2020), raising questions about their pedagogical value beyond convenience. More recent ECE-specific literature, however, highlights ELNs’ ability to capture the process of experimentation—design iterations, decision points, and reflective commentary—rather than solely final results (Higgins et al., 2022; Schröder et al., 2022).
Despite these advantages, the literature also flags issues of cognitive overload and uneven student engagement, particularly when ELNs are introduced without adequate scaffolding. As such, ELNs are increasingly positioned as complementary tools that enhance transparency and feedback in remote laboratories rather than as stand-alone pedagogical interventions (Chen et al., 2024; Gan, 2024).
Portfolios and formative assessment approaches
Portfolio-based assessment has gained renewed relevance in remote laboratory settings as a means of compensating for reduced opportunities for direct observation. Studies in electronics and computer engineering contexts report that electronic portfolios and formative electronic laboratory assessments encourage reflection, creativity, and iterative improvement (Gün-tosik et al., 2023; Rahmawati et al., 2023). However, a recurring critique in the literature concerns assessment burden: poorly aligned or overly complex portfolio requirements can divert student effort away from core technical competencies (Machumu, 2025; Yu, 2026).
Consequently, recent work stresses the importance of careful alignment between portfolio artefacts, learning outcomes, and assessment criteria, particularly in highly technical disciplines such as electronics engineering.
Problem Based Learning (PBL)
Problem-Based Learning reframes laboratory education around extended, open-ended projects designed to mirror professional engineering practice. The literature demonstrates that PBL can substantially enhance student motivation, teamwork, and design thinking in electronics and related fields (Luna and Chong, 2020; Santos-Martín et al., 2011). However, PBL is also resource-intensive and places high demands on instructional design and facilitation. Without sufficient scaffolding, there is a risk that foundational analytical skills may be overshadowed by project management or implementation challenges (Evenddy et al., 2023).
Emerging directions: XR enabled and AI driven laboratories
More recent post-2020 research points toward extended reality (XR) and artificial intelligence (AI) in conjunction with technologies such as digital twins as the next phase of remote laboratory evolution (Akhtar and Rawol, 2024; Alsaleh et al., 2022). XR-enabled laboratories integrate virtual, augmented, and mixed reality to deliver immersive, high-fidelity representations of experimental environments, with early evidence suggesting improved engagement and conceptual understanding alongside persistent concerns regarding accessibility and cost (Haq et al., 2025a). Building on this, AI-driven adaptive laboratory systems introduce intelligent tutoring, dynamic resource scheduling, and personalised feedback pathways, potentially addressing long-standing issues of scalability and individualisation in remote labs (Haq et al., 2025b; Hossain et al., 2023).
While promising, this literature remains largely exploratory, with limited longitudinal evidence of learning gains or institutional sustainability. These gaps underline the need for empirical studies grounded in educator experience to inform realistic adoption pathways.
Synthesis
Collectively, the literature reveals that no single remote laboratory model fully replicates the pedagogical richness of traditional face-to-face laboratories. Instead, the field appears to be converging on hybrid configurations that combine simulations for conceptual grounding, hardware-based approaches for experiential authenticity, and digital tools such as ELNs and portfolios for reflection and assessment. What remains under-explored is how educators evaluate and balance these approaches when multiple options are deployed simultaneously within a single higher education system—a gap this study seeks to address.
Methodology
Research design
This study employed a cross-sectional, mixed-methods survey design to capture how electronic, electrical, and computer engineering lecturers in Irish higher education institutions (HEIs) adapted experiential laboratory teaching during the COVID-19 pandemic. A survey-based approach was selected to enable broad institutional coverage during a period of restricted physical access, while still capturing both quantitative trends and qualitative reflections from practitioners directly responsible for laboratory delivery.
Sample and scope
The survey yielded 33 valid responses from representatives of 12 higher education institutions, drawn from a target population of 18 Irish HEIs offering accredited electronic, electrical, or computer engineering programmes. These institutions span universities and technological universities and include both single- and multi-campus providers.
While the absolute number of respondents is modest, the unit of analysis in this study is institutional practice rather than individual lecturer behaviour. In several cases, respondents reported on approaches adopted at programme or departmental level. Given the relatively small, nationally coordinated Irish higher education sector, coverage of two-thirds of eligible institutions is considered sufficient to identify dominant delivery models and sector-wide trends. Similar sample sizes have been used in comparable national studies of emergency remote teaching during the pandemic.
Survey instrument and validation
Categories and Question Groups used in this Survey.
Prior to full deployment, the survey was piloted with a small group of engineering lecturers not included in the final sample. Feedback from the pilot phase led to minor refinements in question wording and response options. Reliability checks on grouped Likert-scale items yielded an acceptable level of internal consistency, indicating suitability for descriptive analysis.
Data collection
The survey was distributed electronically via institutional mailing lists and professional engineering education networks between January 2021 and February 2021. Participation was voluntary, and responses were anonymised prior to analysis. No personally identifiable data were collected.
Data analysis
Quantitative survey data were analysed using descriptive statistical techniques to identify frequencies and overall trends in adopted laboratory delivery approaches.
Qualitative data from open-ended responses were analysed using a thematic analysis approach. Responses were imported into Qualtrics (via Text iQ) and initially coded using an inductive process to identify recurring concepts. These initial codes were then iteratively refined and clustered into higher-level themes corresponding to delivery models, perceived advantages, perceived limitations, and contextual constraints. To enhance trustworthiness, a subset of responses was independently coded by a second researcher, with discrepancies discussed and resolved through consensus.
Methodology Flow
The overall research process is summarised in Figure 1. Overview of the study methodology.
Results
Background information
Thirty-three respondents from 12 of the 18 targeted higher education institutions completed the online survey, providing institutional coverage across electronic, electrical, and computer engineering programmes in Ireland. The reported teaching experience of respondents ranged from 1 to 46 years, with a mean of 20.7 years and a median of 21.5 years.
The programme structures described reflect typical Irish undergraduate engineering provision. Of the programmes reported, 25% were three-year courses, 69% were four-year courses, and 6% were five-year courses. Most modules referenced by respondents were delivered in earlier stages: 33% at Year 1, 39% at Year 2, and 24% at Year 3, with 3% relating to Year 4 modules.
With respect to laboratory type, 33% of responses described hardware-only laboratory sessions, 9% described software-only laboratories, and 58% described mixed laboratories incorporating both hardware and software elements.
Reported class sizes ranged from 5 to 400 students, with a mean of 63.2 and a median of 45. Student cohort attributes (age band, entry route, and prior laboratory experience) were provided by survey respondents as part of the questionnaire; unless otherwise stated by a respondent, these should be interpreted as lecturer/departmental respondent reports rather than student self-report or administrative records. Based on these respondent-reported figures, most student groups fell within the 18–20 (52%) and 20–25 (45%) age ranges, with 3% reported in the 30–40 age category. Entry profile was reported as 79% general entry, 6% mature students, and 15% other entry routes.
Respondents also reported variation in students’ prior relevant laboratory experience: 42% “none”, 32% “basic”, and 26% “some”, as defined within the survey instrument (e.g., basic experience including prior technical training, and “some” experience including prerequisite modules within the programme).
Pre-covid lab delivery methods
Prior to the Covid-19 pandemic, respondents identified four main approaches to laboratory delivery: traditional, project-based, mixed, and online. Traditional laboratories referred to sessions delivered face-to-face in physical laboratory environments, using institution-based hardware and/or software, typically scheduled as fixed two-hour sessions and assessed through written reports or similar evaluation methods. Project-based laboratories involved students working collaboratively over an extended period on a defined project, with academic staff acting primarily as facilitators during scheduled laboratory time and assessment based on submitted project artefacts or reports. Mixed laboratories incorporated elements of both traditional and project-based delivery within the same module. Online laboratories, by contrast, were delivered remotely to students prior to the pandemic, although this approach was reported infrequently.
The survey results indicate that traditional laboratory delivery predominated in the pre-Covid period. Seventy-five percent of respondents reported using traditional laboratory sessions for module delivery, reflecting established practice within Irish engineering education. Thirteen percent employed project-based laboratories, while 9% reported mixed delivery models combining traditional and project-based elements. A small proportion of respondents (3%) indicated that some laboratory activity was delivered remotely or online prior to the widespread shift to emergency remote teaching, suggesting limited but existing engagement with alternative delivery modes before the pandemic.
Alternative lab delivery methods considered
Alternative laboratory delivery methods: Consideration, implementation, and perceived effectiveness.
Consistent with patterns reported in the literature, learning simulations and remote/virtual laboratory implementations were the most frequently adopted approaches across institutions, programme stages, and laboratory types. For the purposes of analysis, all take-home laboratory kits and physical hardware distributed to students were classified under remote/virtual laboratory implementations. While e-notebooks and portfolios were not actively selected by this cohort, we have included the “perceived” barriers or theoretical drawbacks cited by respondents as reasons for non-adoption of these methods.
To capture lecturer perspectives on effectiveness, respondents were asked to rate the perceived effectiveness of each delivery method using a five-point Likert scale ranging from “Extremely effective” to “Not effective at all”. Figure 2 presents a summary of these responses, providing a descriptive comparison of perceived effectiveness across the different alternative laboratory delivery approaches. Perceived Effectiveness of the different Alternative Lab Delivery Methods.
Evaluative perspectives on lab delivery frameworks
Of the alternative laboratory delivery methods considered, Table 2 summarises those that were ultimately selected for implementation by respondents during the pandemic. The most frequently implemented approach was the use of learning simulations, reflecting both their relative ease of deployment and accessibility. Simulation tools reported by respondents included Proteus, ViciLogic, LTSpice, OrCAD Lite, and TinkerCAD. Survey responses indicated a strong preference for free or readily available software, with one respondent noting that “free was a major motivator to equalise access”. By substituting physical circuit construction with simulated environments, respondents reported that simulations “retained much of the fundamental purpose of the labs”, particularly for conceptual understanding and introductory experimentation.
The second most selected approach was remote/virtual laboratory implementation, most often referring to home or “take-away” laboratory kits. These typically comprised a microcontroller or evaluation board, a breadboard, and discrete components that enabled students to construct and test circuits in a home environment. Respondents reported that such kits helped preserve the “practical and physical approach to engineering” valued by many departments. However, respondents also acknowledged the increased preparation, logistical, and support workload associated with this approach. Despite these challenges, several respondents reported that “adding a physical dimension to labs like this can be very motivating for students” and that home kits provided a valuable platform for independent practical skill development where their provision was feasible.
A third implementation pattern, categorised as “Other”, involved a deliberate combination of simulation-based activities and take-home hardware experiments. In these cases, respondents typically described the use of simulations for initial experimentation, followed by a smaller number of practical tasks conducted using home laboratory kits. This hybrid approach reflects attempts to balance scalability and accessibility with hands-on experiential learning.
The final alternative delivery method selected for implementation was Problem-Based Learning (PBL). Although adopted by only a small number of respondents, PBL was described as supporting contextualised learning and alignment with professional programme outcomes, with respondents suggesting that it “can lead to deeper and more meaningful learning”. Notably, no respondents reported adopting electronic lab notebooks or portfolio-based/formative assessment approaches as primary laboratory delivery methods, although such tools were occasionally referenced as supporting or supplementary elements rather than standalone replacements for laboratory sessions.
Advantages/benefits of chosen delivery method
Perceived categories of advantages for the chosen lab delivery method.
One of the most frequently reported advantages was the ability to maintain continuity of practical laboratory work without requiring student presence in physical laboratories. Respondents noted that remote approaches allowed students to build, test, or simulate circuits and complete experiments, albeit with some limitations. Even where equipment or experimental scope was constrained, the ability to conduct any form of practical activity was viewed positively, with one lecturer noting that the approach “got us very close” to traditional real-world experiences.
A recurring theme across responses was an enhanced student sense of ownership and independence. Lecturers reported that remote delivery reduced opportunities for students to disengage in group settings, as each student was required to demonstrate individual progress and outcomes. Several respondents observed increased depth of individual engagement and learning, supported by the requirement to submit individual artefacts such as video evidence of practical work. Some noted that students appeared to enjoy the remote practical activities, describing them as a welcome change from screen-based learning.
The asynchronous nature of many remote laboratory approaches was also highlighted as a significant benefit. Respondents reported that students could work independently, outside fixed timetables, and revisit materials as needed. This flexibility enabled broader experimentation and reduced constraints typically associated with laboratory access, particularly when supported by simulation tools and online communication with teaching assistants.
Perceived Advantages of chosen lab delivery methods.
Weaknesses/limitations of chosen delivery method
Perceived weaknesses of chosen lab delivery methods.
A frequently reported limitation was the reduced hands-on nature of remote laboratories when compared to traditional laboratory environments. Respondents emphasised that remote approaches were inherently constrained in replicating the physical realities of electronic laboratory work, including exposure to standard equipment, wiring practices, measurement errors, and troubleshooting activities. As one lecturer noted, “there is no substitute for real hands-on measurement and hardware learning.” The absence of tactile interaction was seen as limiting students’ ability to develop practical diagnostic skills.
Issues related to student engagement were also widely reported. Respondents highlighted difficulties in monitoring student progress, identifying disengagement, and providing timely intervention. Several lecturers noted that it was challenging to recognise when students were struggling, particularly in the absence of real-time visual access to students’ work. While some lecturers reported opportunities for focused one-to-one interaction, others cautioned that remote formats could result in uneven demands on instructor time.
In parallel, respondents identified reduced peer-to-peer interaction as a significant drawback. The collaborative dynamics typically observed in physical laboratory settings were reported to be difficult to replicate online, contributing to student isolation. Attempts to recreate group work through online breakout rooms were often hindered by reluctance to participate verbally and by technical issues such as unreliable microphones or connectivity.
Technical and support challenges further compounded these issues. The lack of on-site assistance was perceived as a major limitation, particularly when hardware failures or software configuration problems occurred. Respondents reported that “troubleshooting technical issues remotely is very slow” and that damaged or malfunctioning equipment was difficult to diagnose and resolve without physical access.
Perceived Disadvantages of chosen lab delivery methods.
What would be changed or done differently
Respondents were asked to reflect on what they would change or do differently in future iterations of their laboratory delivery, with the aim of addressing limitations encountered and improving the student experience. Open-ended responses were analysed using an iterative thematic analysis approach (Braun and Clarke, 2006), with several recurring themes identified.
The most prominent theme concerned the expanded use of take-home laboratory kits, often in combination with simulations. Many respondents indicated that they would integrate kits more systematically or transition fully to kit-based approaches in future remote implementations, viewing them as a means of increasing student engagement and interaction with laboratory activities. Respondents already using take-home kits highlighted the need to refine and update kit contents, noting that initial implementations were developed rapidly and were not always optimised. Constraints related to component availability and software compatibility were also cited, prompting some lecturers to reconsider both hardware selection and supporting tools.
A second area identified for improvement related to infrastructure and support requirements for online laboratory delivery. Respondents emphasised the importance of more reliable computing, audio-visual equipment, and network connectivity to reduce bottlenecks and improve the overall experience. This need extended beyond students to include teaching assistants, with several respondents noting that better TA integration would require appropriate equipment and dedicated preparation to support remote troubleshooting effectively.
Improvements to learning materials and assessment design also emerged as a key theme. Respondents reported that the initial development of resources for remote laboratory delivery was time-intensive and that future iterations would benefit from enhanced preparatory materials, such as installation guides, video demonstrations, and FAQs. Several lecturers noted that the experience improved their understanding of online assessment strategies, emphasising the importance of continuous assessment and regular review to identify student difficulties early in an environment where disengagement can be harder to detect.
Finally, not all respondents indicated that changes were either necessary or feasible. Of the 33 participants, six reported that they would retain their current approach for future iterations, citing constraints of the prevailing circumstances or satisfaction with their existing solution. A further four respondents described having limited viable alternatives due to cost or the perceived inefficiency of collaboration-heavy approaches such as PBL in online settings. Notably, one respondent suggested that the enforced transition had revealed that their module “may be more suited to online delivery”.
Discussion
The findings of this study illustrate how Irish engineering educators balanced pedagogical intent with operational feasibility during an unprecedented period of disruption. In line with international literature on emergency remote teaching, respondents described decision-making processes that prioritised continuity, scalability, and institutional resilience, often over idealised pedagogical optimisation. Rather than converging on a single dominant solution, educators adopted a range of pragmatic strategies shaped by contextual constraints, institutional capacity, and the characteristics of their student cohorts.
Comparative matrix of remote laboratory delivery methods.
As shown in Table 7, learning simulations were the most scalable and cost-effective option and were consequently the most frequently implemented. Approximately 70–75% of respondents reported simulations as their primary delivery method, particularly for large-cohort or early-stage modules. They were rated highly for conceptual understanding and rapid iteration but were consistently critiqued for failing to expose students to non-ideal behaviours such as component tolerances, signal noise, wiring errors, or instrument calibration issues.
Take-home hardware kits, by contrast, received the highest ratings for student engagement and practical skill development, with over 60% of respondents indicating a pedagogical preference for hardware-based approaches where resources allowed. However, more than half of respondents implementing kits reported recurring operational difficulties, including faulty power supplies, damaged microcontroller boards, unreliable sensor readings, and variability in students’ home electrical environments. These challenges necessitated substantial additional staff time and often constrained scalability.
Centralised remote laboratories were perceived as technically robust but operationally rigid, while ELNs, portfolios, and PBL were generally described as complementary mechanisms rather than primary substitutes for laboratory experience. Together, these findings reinforce that no single delivery method is universally optimal.
Quantitative, demographic, and contextual influences
Although the study does not claim causal measurement of learning outcomes, combining implementation frequency with perceived effectiveness ratings provides important interpretive context. Simulations were widely adopted but not consistently viewed as sufficient for skill-focused learning, while hardware-based approaches were viewed as effective but operationally demanding.
Respondents also frequently referenced cohort-level characteristics when justifying their method choices. Early-stage undergraduates and students with limited prior laboratory exposure were reported to benefit from the structured nature of simulations, whereas more advanced students or those with vocational experience were better able to engage with open-ended hardware or PBL approaches. These qualitative signals suggest that learner readiness is a critical but under-measured variable in remote laboratory design.
Decision framework for future practice
Decision framework for selecting laboratory delivery approaches.
From the framework in Table 8, several best-practice guidelines emerge: (1) Use simulations as preparatory or baseline tools, particularly for large cohorts. (2) Deploy hardware-based approaches selectively, with explicit logistical planning. (3) Pair experiential activities with structured reflection (ELNs or portfolios). (4) Anticipate and resource for technical failure modes in remote hardware delivery. (5) Design hybrid models intentionally rather than as emergency compromises.
Implications for post-pandemic blended learning
While the data reflect emergency decision-making, respondents indicated that many remote elements—particularly simulations and digital documentation—will persist in post-pandemic blended laboratory models. The findings suggest that future engineering education is likely to combine the scalability and accessibility of digital tools with targeted in-person laboratory experiences, informed by clearer decision frameworks and institutional readiness.
The study’s findings should be interpreted considering known limitations, including voluntary self-selection, heterogeneity of modules, and pandemic-specific constraints. Nevertheless, by embedding comparative synthesis and decision-oriented guidance directly into the Discussion, this work extends beyond descriptive reporting and offers actionable insights for educators and institutions navigating the evolving landscape of experiential engineering education.
Conclusions & future work
This article has examined how electronic and computer engineering lecturers in Irish higher education institutions (HEIs) responded to the rapid and unplanned transition to online and virtual experiential laboratory delivery during the Covid-19 pandemic. Drawing on a descriptive survey of 33 respondents from 12 institutions, the study provides a system-level overview of how practical laboratory teaching was adapted under emergency conditions and offers insights relevant to future engineering education design at both national and international levels.
Survey respondents reported the use of five principal approaches to remote laboratory delivery: learning simulations, take-home or remote hardware laboratory kits, electronic laboratory notebooks or e-books, portfolio-based and formative assessment approaches, and problem-based learning (PBL). Analysis of qualitative and quantitative responses indicates that no single approach emerged as universally preferred. Instead, method selection was strongly conditioned by contextual factors, most notably resource availability, class size, module learning outcomes, and staff support capacity. Learning simulations emerged as the most widely adopted and operationally feasible approach, particularly where time, staffing, or financial resources were constrained and where large student cohorts were involved. In contrast, where resources and support structures permitted—especially in smaller classes—take-home hardware kits were more frequently described as the preferred option due to their perceived effectiveness in supporting practical skill development.
These findings reinforce the view that remote and virtual laboratory approaches should be understood as complementary tools within a broader pedagogical ecosystem, rather than as direct substitutes for traditional face-to-face laboratories. While simulations offer scalability and accessibility, hardware-based and project-oriented approaches preserve key elements of experiential authenticity but introduce substantial administrative and logistical overheads. Electronic lab notebooks, portfolios, and formative assessments were consistently viewed as valuable supporting mechanisms, particularly for reflection, feedback, and documentation, but not as standalone replacements for hands-on laboratory experience.
For policy makers, curriculum designers, and institutional leaders, the results underline the importance of aligning laboratory delivery strategies with realistic operational constraints and explicit learning outcomes. Investment decisions related to digital infrastructure, staff workload, and student support should recognise that different laboratory modalities serve different pedagogical purposes and scale differently. The findings suggest that post-pandemic curriculum design would benefit from intentional hybrid laboratory models, combining simulations, targeted hardware experiences, and digital assessment tools under stable, well-resourced conditions rather than emergency improvisation.
The Covid-19 pandemic constituted an exceptional period in higher education, during which many decisions were made rapidly and under significant uncertainty. Consequently, the findings presented here should be interpreted as lecturer-reported experiences and perceived effectiveness, rather than experimentally validated causal claims regarding learning outcomes. The voluntary nature of the survey, the self-selection of participants, and the heterogeneity of modules and cohorts further limit generalisability.
Future research should therefore extend beyond survey-based approaches to include comparative, longitudinal, and experimental studies that directly evaluate student learning outcomes across different laboratory delivery modes. Such work would provide a stronger empirical basis for determining which combinations of remote, hybrid, and physical laboratory experiences are most effective in post-pandemic engineering education.
Footnotes
Author note
This research was conducted at the University of Limerick, Ireland, within the Department of Electronic and Computer Engineering. There are no conflicts of interest to disclose. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.