Designing Laboratory Sessions in Science and Engineering: A Holistic Framework and Guiding Questions

Practice Paper Recommended citation: Jalali, Y., Langie, G., Verburgh, A., & Dexters, A. (2025). Designing Laboratory Sessions in Science and Engineering: A Holistic Framework and Guiding Questions. In Kangaslampi, R., Langie, G., Järvinen, H.-M., & Nagy, B. (Eds.), SEFI 53rd Annual Conference. European Society for Engineering Education (SEFI), Tampere, Finland. DOI: 10.5281/zenodo.17631469. This Conference Paper is brought to you for open access by the 53rd Annual Conference of the European Society for Engineering Education (SEFI) at Tampere University in Tampere, Finland. This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. Designing Laboratory Sessions in Science and Engineering: A Holistic Framework and Guiding Questions Y. Jalali 1 KU Leuven, LESEC, ETHER, Leuven, Belgium https://orcid.org/0000-0002-1311-2058 G. Langie KU Leuven, LESEC, ETHER, Faculty of Engineering Technology, Sint-Katelijne-Waver, Belgium https://orcid.org/0000-0002-9061-6727 A. Verburgh University Colleges Leuven Limburg, Leuven, Belgium A. Dexters KU Leuven, ELECTA, Faculty of Engineering Technology, Diepenbeek, Belgium Conference Key Areas: Curriculum development and emerging curriculum models in engineering; Open and online education for engineers Keywords: Laboratory, Experimentation, Inquiry, Instructional design, Flexible learning ABSTRACT Over the past few decades, with the rise of educational technologies, educators have reconsidered laboratory instruction by combining various modes of delivery, i.e., hands-on, remote, and virtual laboratories. Despite these innovations, the question of the effectiveness and efficiency of laboratory sessions remains a relevant concern. In this paper, we advocate for reimagining laboratory activities through a three-phase framework consisting of pre-laboratory, laboratory, and post-laboratory phases, and present key questions for each phase of laboratory activities to guide educators in reflecting on essential elements that influence their instructional choices. We argue that the design of any laboratory activity should be considered within a broader, more holistic model of instructional design. Our goal is to spark greater attention to the complexity of laboratory instruction and provide general guidelines for optimizing laboratories and creating more flexible learning pathways. 1 Corresponding Author Y. Jalali [email protected] 1 INTRODUCTION Laboratory work is a crucial component of science and engineering education (Hofstein & Lunetta, 1982; Sheppard et al. 2009). By providing opportunities for practical work, educators often aim to help students solidify their understanding of abstract and complex concepts, develop essential skills related to experimentation and using tools and equipment, and foster a mindset oriented toward inquiry and problem-solving (Edward, 2002; Ma & Nickerson, 2006). However, traditional inperson laboratory formats have some major limitations. They are resource-intensive, requiring ample staff support with high cost associated with preparing and maintaining spaces and equipment, making it increasingly difficult to accommodate a growing number of students. Additionally, the predominant instructional methods in hands-on laboratories, which often rely on predefined, cookbook procedures, have faced criticism. Kirschner and Meester (1988) argued, “There appears to be an overall agreement that laboratory work at present provides a poor return of knowledge in proportion to the amount of time and effort invested by staff and students” (p. 83). This concern remains relevant today, making it imperative to critically reflect about the effectiveness and efficiency of designing laboratory sessions. In recent decades, with the rise of educational technologies, educators have reexamined laboratory instruction by combining different modes of delivery, such as hands-on laboratories and virtual laboratories. These new structures offer greater flexibility, catering to learners from diverse backgrounds (see, for example, Verelst et al. 2009). Empirical studies often demonstrated the added benefits of combining different delivery modes and have advocated for blended learning approaches in laboratory instruction (Makransky & Petersen, 2021; Zacharia, 2007). This argument is supported conceptually by the unique affordances of different learning environments, reducing cognitive load, and opportunities for learning with multiple representations (Ainsworth, 2006; Rau, 2020; Singh et al. 2021; Wörner et al. 2022). However, much of the prior research has primarily compared traditional and nontraditional laboratories (i.e., virtual and remote laboratories) or physical and virtual manipulatives, often overlooking other crucial factors such as learner characteristics, features of learning environments, and experimentation strategies (Bumbacher et al. 2018; Wörner et al. 2022). Additionally, there has been underrepresentation of studies providing an inclusive view of how different learning objectives in laboratory instruction interact with various modes of delivery. Although there is a wealth of research on laboratory instruction in science and engineering, it remains unclear how educators can fully leverage the affordances of different modes of delivery in designing laboratory activities. As part of an Erasmus+ project focusing on creating flexible learning material and developing long-term skill ecosystems in the field of electrification, this paper aims at building a foundation for providing generic guidelines for designing laboratory settings. The project is coordinated by KU Leuven (Belgium) and involves stakeholders from Higher Education (HE) and vocational education and training (VET), industry, research, innovation support organizations, public authorities responsible for education, accreditation, and employment at both regional and national levels. In this paper, we first take a closer look at three major modes of delivery and three different phases that possibly make up a laboratory. And finally, we offer guiding questions to design a laboratory, based on key elements of instructional design frameworks. 2 OVERVIEW OF THE THREE MAJOR MODES OF DELIVERY Broadly speaking, there are three primary types of laboratory modes: hands-on, remote, and virtual (Ma & Nickerson, 2006). In hands-on laboratories, all equipment is physically located in the same space, allowing students to conduct experiments directly in that environment. Remote laboratories, on the other hand, provide access to real equipment and spaces, but the experiment and data collection is carried out from a distance. Finally, virtual laboratories allow students to engage with simulations or imitations of real experiments, often using their computers. The number of non-traditional laboratories has been increasing, in the field of electrical circuits and systems alone we can refer to examples such as NetLab (Gustavsson et al. 2009; http://netlab.unisa.edu.au), the PhET Circuit Construction Kit (https://phet.colorado.edu/), and the VISIR remote lab (May et al. 2020). Each laboratory mode has its own set of advantages and disadvantages. Hands-on laboratories can be particularly effective in developing students’ practical skills. They help students learn by doing, enhance their problem-solving abilities, promote motor skills through handling materials, and provide opportunities to confront experimental errors and unexpected challenges (Brinson, 2015; Wörner et al. 2022). However, they can be costly, time-consuming, and present safety concerns, especially when students are exposed to potentially hazardous materials and complex equipment for the first time. Remote laboratories offer the convenience of access without time and location limitations. The resources can be shared and allow for repetition and facilitating deep learning (Brinson, 2015). However, they pose challenges in terms of maintenance and scheduling, as managing resources and coordinating access for students can be complex. Moreover, these remote laboratories are not feasible for all tasks since physical presence in the lab is sometimes essential. Despite these challenges, remote laboratories provide a valuable alternative for educational settings where access to physical settings is restricted. Virtual laboratories, while limited in offering real-world experiences, have the advantage of providing students with access to numerous examples and opportunities for iteration. They also allow students to visualize phenomena and processes that might otherwise be beyond their perception (Bumbacher et al. 2018; Heradio et al. 2016). These laboratories are especially useful in scenarios where there are cost or safety concerns. However, they do not provide the real-life experiences of hands-on laboratories. Simulations and virtual environments can benefit from the advances in technology to create a more realistic experience and increase students’ engagement. For example, immersive virtual reality, which uses a head-mounted display, is commonly employed in interventions with engineering students (Zontou et al. 2024). However, it should be noted that while immersive virtual reality may enhance the sense of presence, its impact on students’ learning is still debated, as it may increase extraneous cognitive load, for instance see Makransky et al. (2019). Overall, it is often advisable to take advantage of different modes of delivery, as they offer unique and useful affordances (Rau, 2020; Wörner et al. 2022). As Heradio et al. (2016) argued, “virtual, remote, and hands-on laboratories are not mutually exclusive; they can be integrated and complement each other in a single learning unit” (p.16). For experiencing motor skills, for example, using concrete materials and equipment is beneficial, while for repeating accurate measurement an error-free measurement environment may be more suitable (Zacharia, 2007). There is growing evidence of students’ improved achievement when combining non-traditional and traditional modes of delivery, particularly in terms of conceptual understanding (e.g., Jaakkola et al. 2011; Kapici et al. 2019; Zacharia, 2007; Zacharia et al. 2008). While these findings are scientifically valuable, their practical application should be approached with a healthy degree of skepticism. Bumbacher et al. (2018) highlighted limitations in empirical studies, noting that they often fail to adequately consider the inquiry process in addition to the outcomes, and overlook the unique affordances of different mediums, which can vary in more than one aspect. More recently, Gavitte et al. (2024) argued that instructional design must leverage the affordances of various modes of delivery. They identified three key features critical to the effectiveness of combining physical and virtual laboratories: i) order, the order in which activities are completed, ii) degree of replication, how closely objectives, conditions, and parameters are replicated across modes, and iii) prescription, the extent to which process parameters are prescribed. In practice, the affordances of learning environments interact with students’ characteristics, pedagogical approaches, and the methods used to guide them. Furthermore, simply repeating the same activities or conducting different experiments across various mediums does not necessarily provide insights into designing a comprehensive experimental learning activity that fully leverages the affordances of both non-traditional and traditional laboratories. 3 OVERVIEW OF THE THREE PHASES OF A LABORATORY ACTIVITY While providing detailed, generic guidelines considering all the elements of a laboratory is beyond the scope of this paper, we aim to suggest a necessary structure for any laboratory activity. We advocate for reimagining laboratory activities through a pre-laboratory, laboratory, and post-laboratory structure. The pre-laboratory phase should focus on refreshing prior knowledge, introducing necessary concepts, preparing measurements (instrumentation, calculation sheets, etc.), facilitating critical reflection, and providing feedback. Previous literature has addressed the use of non-traditional modes prior to in-person, hands-on laboratories, recognizing it as a form of pre-training that benefit students by increasing their confidence and self-efficacy, familiarizing them with key concepts, and reducing cognitive load (Abdulwahed & Nagy, 2009; Makransky et al. 2016; Meyer et al. 2019; Seery et al. 2019; Singh et al. 2021; Verelst et al. 2009). The laboratory phase refers to the in-person, (hands-on) stage, which can be implemented as needed. The post-laboratory phase focuses on facilitating critical reflection, data analysis, written reports and presentations, emphasizing additional concepts and providing feedback. The three-phase framework is being used in several laboratories at KU Leuven, including the Biochemistry and Cell Biology Laboratory (Borremans et al., 2024) and the Chemical Lab Techniques (Szekér, 2025), among others. Pre-laboratory activities are designed to prepare students both cognitively and affectively for in- person sessions, thereby allowing more time for hands-on practice and deeper engagement during contact hours. For example, in the Biochemistry and Cell Biology Laboratory, students are required to undertake extensive preparation prior to each session. Instructors encourage students to (i) engage in self-reflection by posing critical questions and anticipating possible answers, and (ii) independently research relevant information in advance (Borremans et al., 2024). At the beginning of each lab session, students complete a quiz that assesses both theoretical understanding and knowledge of experimental procedures. Notably, some studies advocate prioritizing supportive information—such as underlying theory and the rationale for particular experimental approaches—over procedural instructions during the prelaboratory phase (Agustian & Seery, 2017). The structure of the laboratory phase can vary depending on several factors, including the level of prescription, the quantity and quality of pre-laboratory information, the inductive or deductive nature of the experimentation, and whether outcomes are predetermined or exploratory (Domin, 1999; Domin, 2007). In the context of experimental physics, Smith & Holmes (2021) argued that laboratories should embrace complexity and serve the experiment rather than theory. For instance, if the primary objective is to understand a physical model, demonstrations or simulations may be more appropriate than hands-on experimentation (Smith & Holmes, 2021). Overall, while student agency and engagement should remain central, there is no universal model for structuring the contact phase; approaches must be adapted to the specific domain, experimental setup and procedure, and learning objectives. The post-laboratory phase should be regarded not merely as a mechanism for assessing student achievement, but as an integral component of the learning process. Within the inquiry-based learning framework proposed by Pedaste et al. (2015), communication and reflection are considered ongoing processes applicable to various phases of inquiry pathways. Put differently, opportunities for reflection, for instance, should be embedded throughout the learning experience. 4 DESIGNING A LABORATORY SESSION: A HOLISTIC CONCEPTUALIZATION We argue that designing laboratory experiments, like any other learning activity, should be informed by instructional design frameworks, aligning key elements such as student characteristics, learning objectives, learning activities, learning environments (including materials, instructional methods, and scaffolding tools), and assessment (Biggs, 2003; KU Leuven Learning Lab, 2024), and guiding questions to help educators make decisions in each phase. At a more macro-level understanding students’ characteristics and identifying learning objectives are essential. When considering students’ characteristics, we highlight the importance of prior knowledge. This is critical for adjusting pedagogical approaches to support students’ learning and help bridge existing and new knowledge. Cognitive learning theories emphasize the role of learners in constructing and reconstructing their own understanding when encountering new experiences (Prince & Felder, 2006). Learning is stimulated when prior knowledge is activated, and students can confirm or correct existing mental models, leading to changes in their understanding (Lattuca & Stark, 2009; Newstetter & Svinicki, 2014). Therefore, it is crucial to focus on the role of the learner, their existing knowledge, and to create opportunities for active engagement. Graphical tools, such as concept maps, can help organize knowledge by representing core concepts and their relationships (Novak & Cañas, 2008; Jackson et al. 2023). These tools aid students in visualizing and understanding the content, linking new information with prior knowledge, and providing a basis for reflection, discussion and assessment. Regarding learning objectives, formulating clear objectives is one of the most important steps in designing any learning activity, providing a roadmap for educators in designing effective learning activities and assessments. Olympiou & Zacharia (2012), in their framework for blending physical and virtual learning environments, emphasized the alignment of learning objectives with the affordances of each environment for specific experiments. Similarly, Heradio et al. (2016) highlighted that the choice of delivery mode is influenced by the learning objectives (Heradio et al. 2016). Several frameworks are widely used to address laboratory learning objectives in science and engineering (Brinson, 2015; Edward, 2002; Feisel & Rosa, 2005; Ma & Nickerson, 2006; Nikolic et al. 2021; National Research Council, 2006). Common learning objectives include understanding key concepts, solving problems through the design and construction of new artifacts or processes (Ma & Nickerson, 2006), identifying unsuccessful outcomes and re-engineering effective solutions, and demonstrating competence in selecting, modifying, and operating appropriate engineering tools and resources (Feisel & Rosa, 2005). Laboratories can also serve as effective environments for fostering students’ transversal competencies, such as teamwork and communication, although their explicit integration requires systematic instruction; see, for instance, Isaac et al. (2024) and Jalali et al. (2024). On a micro level, several principles apply regardless of the phase or delivery mode. In contrast to the cookbook approach to laboratory instruction, which often fails to promote deep learning or higher-order cognitive skills (Domin, 1999), researchers advocate for exposing students to open-ended situations. These situations give students more responsibility for the learning process, encouraging them to design experiments, collect data, and analyze results (Kapici et al. 2022; Ma & Nickerson, 2006). Felder and Brent (2024) argued that achieving intended learning objectives is not possible with “carefully scripted experiments”, and educators need to move away from detailing every step and spelling out everything students need to do. The authors recommended assigning fewer experiments but adopting open-ended format with minimum instruction (Felder & Brent, 2024). For instance, when designing experiments, students may be asked to specify the dependent, independent, and control variables, and select specific values for independent variables (van Riesen et al. 2022). In designing inquiry-based activities, then, it is necessary to carefully consider students’ prior knowledge and the level of guidance provided. It is reasonable to speculate that advanced learners, in contrast to novices, require less direction to navigate the complexity of the learning process. Specific instructional approaches such as Predict-Observe-Explain (POE) (Al Mamun et al. 2020; Felder & Brent, 2024) can serve as scaffolding tools to support students’ learning. POE involves students predicting the results of experiments, conducting the experiment, and examining differences between predictions and observations. This strategy can also be used as a springboard for discussion, correcting misconceptions, and promoting conceptual understanding (Felder & Brent, 2024). Furthermore, to design effective laboratories—regardless of the mode of delivery— students should be provided with opportunities to actively engage with learning materials; this includes navigating the environment, adjusting and manipulating variables, observing the resulting changes, and troubleshooting, as well as reflecting on their experiences. In addition to interactions with learning materials, studentcontent interactions, educators should also consider other dimensions of engagement, including student-student and student-teacher interactions (Moore, 1989), for example by providing opportunities for group work, and communication and discussion in forums. Encouraging students to pose targeted questions, along with structured discussions and briefings prior to the experiment, for instance, promotes engagement across multiple dimensions. While the type of questions educators should consider when making decisions follows from the discussion so far, this does not deter us from suggesting several guiding questions for each phase in designing a laboratory activity (Figure 1). 5 DISCUSSION AND CONCLUSION In this paper, we proposed adopting a comprehensive approach to laboratory instruction in science and engineering education, using three phases of prelaboratory, laboratory, and post-laboratory. While this structure is not novel, see for instance Verelst et al. (2009), we would recommend employing the three-phase framework for designing each laboratory activity. We argue that the question of selecting modes of delivery (the “what”) cannot be separated from how these modes are used and integrated into the design of laboratory activities (the “how”). In other words, the choice of delivery mode is not solely influenced by contextual factors like cost or safety; rather, the design of any laboratory activity should be considered within a broader, more holistic model of instructional design that serves as a starting point for a process-oriented approach that emphasizes the mechanisms and procedures that influence students’ learning, including student characteristics and learning objectives, learning activities and support provided to students. Fig 1. Three-phase framework for laboratory activities and guiding questions There are several reasons to believe that hands-on laboratories will continue to play a vital role in science and engineering education. They address the crucial need to connect theory with practice, provide opportunities for working with tools and equipment, and foster creativity and problem-solving when students encounter discrepancies or unexpected results. Meanwhile, the use of technology, such as simulations or instructional videos, has grown as a supplement or pre-laboratory activity. The challenge remains in effectively integrating the various resources available to educators. We presented key questions for each phase of laboratory activities to guide educators in reflecting on essential elements that influence their choices. At the core of these questions is the importance of student agency and engagement (Makransky & Petersen, 2021; Moreno & Mayer, 2007; Zacharia, 2007). As such sustaining student motivation throughout the learning process is essential. Effective strategies include incorporating inquiry-based learning, using methods such as POE (PredictObserve-Explain), posing open-ended questions to encourage student explanations, and providing multiple opportunities for reflection, discussion, and feedback. However, considering the diversity in students’ profiles and the complexity of the equipment and experiments, educators must adopt strategies that connect learning content to students’ interests and backgrounds, activate and link prior knowledge to new materials, and highlight the authenticity of the tasks and practical significance of what students will experience in the experiment. The three-phase framework encourages educators to adopt a more holistic approach in utilizing various resources. Given the presence of advanced yet costly facilities, the constraints of experimental procedures, and the limited availability of time, improving efficiency and ensuring accessibility for diverse student groups have become pressing concerns. Intensive short-time access to laboratories, for instance, has been implemented as part of multicampus programs (Wuyts et al. 2015). Overall, incorporating such holistic approach is an essential step for optimizing laboratories to create more flexible learning pathways, supporting learning mobility and opportunities for lifelong learning, and addressing the diverse needs of students at different European Qualifications Framework (EQF) levels. While the benefits of explicit integration of the model on the efficiency are evident, its impact on the effectiveness of laboratory sessions requires further empirical validation. Here, we reiterate the inherent complexity of evaluating learning environments considering both processes and outcomes (Bumbacher et al. 2018), as well as the need for paying close attention to research design in any comparative study (Domin, 2007; Hofstein & Lunetta, 1982). Although this work is still conceptual, we hope it will catalyze attention to the complexity of laboratory instruction. To make the discussion more relevant to science and engineering educators, a more in-depth analysis of specific activities is necessary. Our future work will focus on examining several laboratory settings, expanding the guidelines and proposing specific recommendations for redesigning laboratory activities. ACKNOWLEDGMENTS We would like to thank Inge Holsbeeks, Kathelijne Szekér, Lieven De Smet, and Martijn van Bommel for their valuable feedback and constructive comments.