How did these experts-in-training practice safely, not hurting themselves or anyone else in the process? Simulations. The solution of incorporating simulated learning experiences into education sounds simple but is it? No! Simulated learning platforms must be imagined and built, tested and improved, and, importantly to Labster, research-driven.
Labster co-founders Michael Bodekaer Jensen and Mads Bonde identified the potential for quality simulations for learning science and then leveraged research to find a solution in virtual labs. Inspired by aviation training’s use of flight simulations, Jensen and Bonde used research-informed practices to design a platform that allowed students to practice experiments from home. The co-founders wanted to support students in developing high-level laboratory skills without the typical constraints of in-person lab study such as scheduling, staffing, supplies - and even safety.
Labster’s inspiration from flight simulators (1) was only the beginning of using innovation to inform development and product improvements. Recognizing the importance of research-informed learning practices, Labster was built on a rigorous, evidence-based foundation to drive student learning outcome attainment.
Labster provides a flexible approach to learning that applies all of the best aspects of explicit instruction, inquiry-based learning, and problem-based learning. Virtual lab simulations help students connect theory with practice as well as visualize processes, practical laboratory procedures, and instrument techniques. (2)
The Labster team’s goal is to build simulations that confer the benefits of traditional explicit instruction to students in a setting that empowers them with choice and maintains attention by matching the instructional method with the learner's comfort level. Inquiry-based learning is a student-centered method in which students discover new things by exploring their near environment and developing strong arguments about the world surrounding them based on strong justifications. Research shows that inquiry-based learning is very effective within science learning (3) since the work is simultaneously creative and practical.
Over the years, Labster's approach to creating curriculum shifted from building specific simulations for school curriculums to designing their own learning objectives that employed Problem-Based-Learning. While inter-connected with Inquiry-Based-Learning, PBL is focused on giving students complex problems to solve, whereas IBL is more commonly associated with giving students choice research opportunities. PBL has also been shown to be specifically effective when teaching science. (4)
The Labster team integrated the strategy of students creating solutions within realistic constraints. PBL comes to life in Labster’s Behavioral Thermoregulation simulation where students create their own planet and try to maintain life on the planet. The key to this learning strategy is that there are multiple solutions, and not necessarily a right or wrong answer. Students' engagement and knowledge building increase when students can explore real-world problems such as exploring the nitrogen cycle to maintain proper crop yields to feed the population but not overheat the planet by manipulating water and fertilizer cycles.
Labster’s virtual lab environment provides immediate feedback to improve the impact on student achievement (5) and motivation for learning (6). Students get feedback the second they complete something correctly or incorrectly, increasing their rate of learning. Incorporating user feedback, the design team enhanced the way success and failure within sim experiences are communicated, creating new design guidelines for all simulations that better fit the research-informed feedback student evaluation models. (7) These feedback loops enable active learning to be productive and advance learning outcomes.
Labster operationalizes multimodal instruction to meet the diverse needs of learners through multiple points of exposure and forms of practice. Different activities within the sim experience around the same topic including readings, experimental procedures, testing yourself, and model making maximize learning outcomes. Research demonstrates that multimodal instruction allows for increased practice and multiple entry points to the content particularly useful for diverse learners. (8)
The Labster team created and utilizes a research-informed mechanic called Dr. One, a virtual lab assistant, to show student users how to complete a task prior to trying it themselves (similar to a worked examples) and remind students about lab safety. Research suggests that students learning with virtual helpers or “pedagogical agents” has a positive effect on learning outcomes (9) perhaps by reducing the cognitive load on the learner.
This is particularly true when the pedagogical agent allows for students to experience worked examples in combination with their own problem-solving (10).
Labster’s virtual labs and science simulation automatically individualize instruction to a student’s learning needs. Labster’s responsive model and self-paced approach tap into the improved learning outcomes reflected in the research (11) on individualized learning approaches. The integration of Universal Design for Learning throughout the simulations also increases equity in access within Labster’s programming, specifically making improvements to their hardware and software for the visually and hearing impaired.
Meta-analyses conducted on the experiments cited in the above topics outperform most educational strategies (less than .40 is low). Of the pedagogical strategies utilized by Labster, individualization has shown the highest impact within research, followed by problem-based and inquiry-based learning. Simulation and platform learning with immediate feedback also outperform most educational strategies in terms of the magnitude of their effect on learning outcomes.
Labster is built on a foundation of research but is not solely research-based. The program is also an evidence-based product that has been rigorously tested and improved over time. The program has had over 21 peer-reviewed studies, including nine randomized control trials, three quasi-experimental studies, three case studies, and four survey studies. All studies showed a positive benefit, with the largest benefits shown in knowledge building, enjoyment, and lab applications. Labster has also been shown to be especially helpful for struggling learners. Take a look at this chart showing some of the impacts found in Labster’s research ranked by effect size.
Over two thousand learning institutions currently use Labster’s innovative and evidence-driven platform. The Labster team has demonstrated a clear commitment to the science of learning, both by continually incorporating science into their product design and through continual scientific experimentation on their own product. Scientific research is woven into the culture at Labster as we design simulations that are engaging, build confidence, and transfer new skills to the real world.
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(2) De Vries, L. E., & May, M. (2019). Virtual laboratory simulation in the education of laboratory technicians–motivation and study intensity. Biochemistry and Molecular Biology Education, 47(3), 257-262.
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(4) Ayaz, M.t & Söylemez, M. (2015). The Effect of the Project-Based Learning Approach on the Academic Achievements of the Students in Science Classes in Turkey: A Meta-Analysis Study. Eğitim ve Bilim. 40. 255-283.
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(7) Schinske, J., & Tanner, K. (2014). Teaching More by Grading Less (or Differently). CBE life sciences education, 13(2), 159–166. https://doi.org/10.1187/cbe.cbe-14-03-0054
(8) Ryoo, J., & Winkelmann, K. (2021). Innovative learning environments in STEM higher education: Opportunities, challenges, and looking forward (p. 137). Springer Nature.
(9) Schroeder, N. L., & Craig, S. D. (2021). Learning with virtual humans: Introduction to the special issue. Journal of Research on Technology in Education, 53(1), 1-7.
(10) McLaren, B. M., & Isotani, S. (2011, June). When is it best to learn with all worked examples?. In International conference on artificial intelligence in education (pp. 222-229). Springer, Berlin, Heidelberg.
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