Enhancing Learning in Microelectronic Circuits: Integrating LTspice Simulations and Structured Reflections in a Design Project
Abstract
1. Introduction
1.1. Research Objective and Questions
- How do LTspice simulations and structured reflective practices influence students’ conceptual understanding of microelectronic circuits?
- How do these practices impact students’ problem-solving abilities when engaging in circuit design and analysis?
- How does the integration of simulations, reflections, and PBL affect students’ engagement and motivation in the course?
- What challenges and benefits arise from incorporating LTspice simulations, reflective practices, and PBL into the curriculum?
1.2. Theoretical Background
1.2.1. Challenges in Teaching Microelectronic Circuits
1.2.2. Simulation Tools in Engineering Education: Benefits and Limitations
- They visualize dynamic circuit behavior, such as waveform propagation, logic transitions, and signal delays (Rivera-Reyes et al., 2017).
- They provide a risk-free environment to test ideas and experiment with designs without damaging physical components (Tenzin et al., 2023).
- Immediate feedback allows iterative refinement and supports students’ problem-solving skills (Dormido et al., 2008).
- LTspice’s free and lightweight design promotes flexible learning outside of scheduled lab hours (Coller & Scott, 2009).
1.2.3. Simulation-Based Learning in Active Learning Pedagogies
- Magana and de Jong (2018) and Vlachopoulos and Makri (2017) showed improved student engagement and motivation.
- Rivera-Reyes et al. (2017) demonstrated enhanced conceptual understanding in LTspice-supported analog design courses.
- Harris and McPherson (2017) found that students using PSpice developed stronger analog troubleshooting skills.
1.2.4. Toward an Integrated Framework: Simulation, Reflection, and PBL
- Cognitive: LTspice simulations facilitate the visualization of circuit behavior and support the development of system-level thinking (Rashid, 2024; Salovirta, 2024).
- Metacognitive: Reflective writing encourages students to monitor and regulate their thought processes, recognize patterns of error, and develop more strategic approaches to learning (Dickerson & Clark, 2021; Magana & de Jong, 2018).
- Collaborative: PBL fosters teamwork, communication, and the co-construction of engineering knowledge through group decision-making and shared troubleshooting (Issa et al., 2023).
2. Materials and Methods
2.1. Participants
2.2. Course Design and Intervention
- LTspice simulations: The students completed simulation assignments involving circuit design, analysis, and optimization. These assignments focused on key concepts such as small-signal modeling, frequency response, and transient analysis. Each simulation assignment was a step in the development of a comprehensive final project.
- Reflective practices: After completing each simulation assignment, the students submitted written reflections analyzing their progress. Reflection prompts encouraged the students to evaluate their understanding of circuit behavior, identify challenges, describe their problem-solving strategies, and connect their work to the overall project goals. These reflections aimed to enhance metacognitive awareness and critical thinking.
- PBL framework: The assignments were embedded within a semester-long capstone project that required the students to design, simulate, and analyze a complex circuit system, simulating real-world engineering challenges. The PBL framework emphasizes iterative improvement, collaboration, and the practical application of theoretical knowledge.
- Curricular adjustments: Lecture time was reduced to accommodate interactive learning sessions. Simulation labs, group discussions, and reflection activities allowed the students to actively engage with the material, fostering deeper learning and skill development.
2.3. Data Collection
- Reflective journals: After completing each LTspice simulation assignment, the students were required to submit written reflections, which were intended to promote metacognitive thinking and self-assessment (Shekh-Abed, 2024). Reflection prompts were designed to assist the students in explaining their learning experiences, obstacles they encountered, problem-solving tactics they used, and insights gained from the simulations.
- Participant observations: The course instructor, who was also the primary researcher, engaged in participant observation throughout the project session. Field notes were systematically recorded during lab sessions, team discussions, and project presentations. These observations focused on student engagement, collaborative behavior, debugging strategies, and expressions of understanding or misconceptions.
- Assignment reports: The students were required to submit four project-related assignment reports over the course of the semester. These reports documented each phase of the design process, including simulation setup, circuit testing, iterative design changes, and final implementation. The reports provided valuable technical artifacts for analyzing the evolution of the students’ reasoning and problem-solving across the project timeline.
- Final project presentations (exam): At the end of the semester, the students presented their final projects, which were based on the accumulated knowledge and abilities learned throughout the course, including the use of LTspice. During this presentation, the students had to display their projects and respond to questions posed by the course instructor. This final exam functioned as both an assessment of the students’ comprehension and an opportunity for them to communicate and share their problem-solving processes and design decisions.
2.4. Procedure
- Building a 4-bit DAC: The students were charged with developing and simulating a 4-bit DAC using LTspice, allowing them to put theoretical concepts into practice.
- Implementing ADC components at a high system level: This assignment required the students to design and simulate ADC components at the system level, helping them better grasp high-level circuit design.
- Integrating ADC components at a high system level: The students were asked to integrate previously built ADC components into a bigger system, which helped them comprehend system-level design and integration.
- Implementing transistor-level components and integrating them into ADCs: This assignment required the students to focus on transistor-level design and integration into ADC systems, bridging the gap between low-level component design and high-level system operation.
- What key principles did you learn from this simulation assignment?
- Describe any difficulties you faced. How did you handle these challenges?
- How do you think this simulation assignment improved your grasp of the theoretical concepts covered in the lectures?
2.5. Data Analysis
- Data familiarization: The first stage was to read the students’ reflections, researcher observations, and assignment reports several times to become familiar with the topic. This technique enabled the researcher to detect initial patterns and repeating themes in the data.
- First cycle—Open coding: Using an inductive strategy, the researcher manually assigned codes to meaningful segments of the text without relying on a predefined coding structure. The codes captured recurring phrases, concerns, strategies, and learning insights.
- Second cycle—Focused coding: A deductive approach was then employed, drawing on relevant theoretical constructs from the simulation-based and active learning literature (Yin, 2009). The codes were refined and grouped into broader categories aligned with the study’s research objectives—such as conceptual understanding, problem-solving strategies, metacognitive reflection, and student engagement.
- Theme development: The codes were organized into larger themes that reflected the core of the students’ educational experiences. Themes such as “enhanced conceptual understanding,” “improved problem-solving skills,” “increased engagement and motivation,” and “challenges in using LTspice” were created to arrange the data.
- Theme refinement: The themes were examined and adjusted to ensure they accurately reflected the facts. This stage entailed re-examining the coded material within each topic to ensure consistency and coherence. Themes that were overlapping or too broad were separated or combined to provide a more complete picture of the findings.
- Peer review and trustworthiness: To enhance credibility, an external researcher with expertise in engineering education independently coded a random 25% sample of the reflections. An inter-coder agreement of approximately 82% was reached. Discrepancies were resolved through discussion, which led to final adjustments in the thematic structure.
- Interpretation and reporting: The final phase of the analysis entailed interpreting the themes in light of the study questions and the available literature. The interpretation focused on how the combination of LTspice simulations affected the students’ learning outcomes, specifically conceptual understanding, problem-solving abilities, and engagement. The findings were then presented, with example extracts from the students’ reflections and final project presentations to corroborate the analysis.
2.6. Validity and Reliability
- Triangulation: Using various data sources—self-reflections, researcher observations, assignments reports, and final project presentations—provided a holistic picture of the students’ learning experiences, increasing the validity of the findings (Patton, 1999).
- Peer review: A peer with experience in qualitative research assessed the data analysis procedure. This review contributed to the rigorous coding and theme creation processes, as well as to the credibility of the findings (Creswell & Miller, 2000).
- Reflexivity: Throughout the study, the researcher kept a reflective record, documenting any potential biases or assumptions that may have influenced the data interpretation. This method helped reduce researcher bias and maintain objectivity throughout the analysis (Yin, 2009).
3. Results
3.1. Thematic Analysis Results
- T1: Theory–Practice Link—Reflections coded under this theme emphasized how the students used LTspice simulations to connect abstract theoretical content—such as analog-to-digital conversion—with observable circuit behavior.
- T2: Iterative Strategy—This theme captured the students’ trial-and-error approaches, parameter tuning, and resimulation strategies to improve circuit functionality.
- T3: Metacognitive Awareness—Entries in this theme reflected the students’ recognition of their own mistakes, reasoning processes, and learning strategies—indicative of higher-order thinking.
- T4: Peer Learning and Engagement—This category included reflections on collaboration, mutual feedback, and the emotional dimensions of teamwork and simulation-based learning.
- T5: Integration Reflections—Reflections in this category dealt with challenges and benefits of combining LTspice simulation, structured reflection, and PBL into the curriculum. The students highlighted moments of frustration as well as insights gained from working through integrated project tasks.
3.2. Enhanced Conceptual Understanding (RQ1)
“Before the simulation, I struggled to understand how the SAR ADC worked. Seeing the SAR update step-by-step in response to the comparator’s output, helped me visualize how digital conversion happens in real time.”
“I never realized how important the DAC’s role is in refining the ADC’s accuracy until I saw how changing the reference voltage affected the resolution of the output.”
“Before running the simulation, I assumed my ADC would capture the sine wave input perfectly. But when I saw the step-like output, it finally clicked why higher bit resolution reduces quantization error.”
“The simulation showed how a slow sampling rate leads to aliasing, something I understood only mathematically before.”
“Seeing how the clock speed affects conversion rate and resolution in the SAR ADC helped me understand why high-speed ADCs are used in some applications while lower-speed ADCs work for others.”
3.3. Enhanced Problem-Solving Abilities (RQ2)
3.3.1. Iterative Strategy: Practical Problem-Solving Engagement
“I initially made an error in my resistor divider, which threw off my reference voltage. Seeing the incorrect waveform in the simulation helped me diagnose the problem quickly.”
“I realized that changing a comparator’s threshold had a bigger impact on ADC accuracy than I expected. The simulation helped me fine-tune it systematically.”
3.3.2. Metacognitive Awareness: Reflection on Thinking and Learning
“Writing down my thought process after each simulation helped me realize patterns in my mistakes. Instead of making the same error multiple times, I started anticipating problems before they occurred.”
“Using LTspice taught me that designing an ADC involves more than just applying formulas; I needed to understand how adjusting one component, such as a comparator or resistor, could impact the entire conversion process and overall performance.”
3.4. Enhanced Engagement and Motivation (RQ3)
“The ability to experiment with various designs and instantly observe the outcomes consistently intrigued and pushed me to continue my studies.”
“The simulations made me feel like I was really in charge of the design. I could try things and immediately see what worked.”
“My teammate’s explanation helped me finally understand what was wrong with our DAC. We figured it out together.”
3.5. Addressing Implementation Challenges (RQ4)
“Initially, I encountered considerable difficulty using LTspice. The abundance of options and settings overwhelmed me, leaving me unsure of where to begin. The experience was exasperating, as I found myself devoting more time to deciphering the software rather than gaining knowledge about circuits.”
“Occasionally, I would persistently adjust the parameters of the SAR ADC simulation until it produced the desired conversion results, yet I didn’t always fully understand the underlying principles that made it work.”
4. Discussion
4.1. Enhanced Conceptual Understanding
4.2. Better Problem-Solving Abilities
4.3. Greater Engagement and Motivation
4.4. Addressing Implementation Challenges
4.5. Limitations and Future Research
5. Conclusions
- Designing structured learning pathways for LTspice proficiency to help students overcome initial technical barriers and develop confidence in using simulation tools.
- Embedding reflective learning exercises that encourage students to analyze and articulate their troubleshooting strategies, reinforcing deeper conceptual understanding.
- Encouraging collaborative problem-solving activities, enabling students to engage in peer discussions and share insights, in turn fostering a more dynamic and interactive learning environment.
- Integrating simulations with hands-on lab work and theoretical instruction to create a balanced and holistic educational approach that supports the development of both analytical and practical skills.
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Ash, A., & Hu, J. (2024). Improving high school math engagement with circuit and transistor examples. In 2024 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1–5). IEEE. [Google Scholar]
- Biggs, J., & Tang, C. (2011). Teaching for quality learning at university. McGraw-Hill Education. [Google Scholar]
- Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn (vol. 11). National Academy Press. [Google Scholar]
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. [Google Scholar] [CrossRef]
- Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020). Simulation-based learning in higher education: A meta-analysis. Review of Educational Research, 90(4), 499–541. [Google Scholar] [CrossRef]
- Coller, B. D., & Scott, M. J. (2009). Effectiveness of using a video game to teach a course in mechanical engineering. Computers & Education, 53(3), 900–912. [Google Scholar] [CrossRef]
- Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory Into Practice, 39(3), 124–130. [Google Scholar] [CrossRef]
- Dai, C.-P., & Ke, F. (2022). Educational applications of artificial intelligence in simulation-based learning: A systematic mapping review. Computers and Education: Artificial Intelligence, 3, 100087. [Google Scholar] [CrossRef]
- Deci, E. L., & Ryan, R. M. (1985). Conceptualizations of intrinsic motivation and self-determination. In Intrinsic motivation and self-determination in human behavior (pp. 11–40). Springer US. [Google Scholar]
- Dewey, J. (1933). How we think: A restatement of the relation of reflective thinking to the educative process (Vol. 8). D.C. Heath. [Google Scholar]
- Dickerson, S. J., & Clark, R. M. (2018). A classroom-based simulation-centric approach to microelectronics education. Computer Applications in Engineering Education, 26(4), 768–781. [Google Scholar] [CrossRef]
- Dickerson, S. J., & Clark, R. M. (2021). Use of SPICE circuit simulation to guide written reflections and metacognition. IEEE Transactions on Education, 65(3), 471–480. [Google Scholar] [CrossRef]
- Dori, Y. J., Dangur, V., Avargil, S., & Peskin, U. (2014). Assessing advanced high school and undergraduate students’ thinking skills: The chemistry—from the nanoscale to microelectronics module. Journal of Chemical Education, 91(9), 1306–1317. [Google Scholar] [CrossRef]
- Dormido, S., Vargas, H., Sánchez, J., Dormido, R., Duro, N., Dormido-Canto, S., & Morilla, F. (2008). Developing and implementing virtual and remote labs for control education: The UNED pilot experience. IFAC Proceedings Volumes, 41(2), 8159–8164. [Google Scholar] [CrossRef]
- Fares, D. A., Joujou, M. K., Khaddaj, S. I., & Kabalan, K. Y. (2012, April 17–20). A learning approach to circuitry problems using MATLAB and PSPICE. 2012 IEEE Global Engineering Education Conference (EDUCON) (pp. 1–5), Marrakech, Morocco. [Google Scholar]
- Felder, R. M., & Brent, R. (2005). Understanding student differences. Journal of Engineering Education, 94(1), 57–72. [Google Scholar] [CrossRef]
- Harris, T., & McPherson, J. (2017). Enhancing analog electronics education through the use of PSpice simulations. IEEE Transactions on Education, 60(2), 134–141. [Google Scholar]
- Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: A response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107. [Google Scholar] [CrossRef]
- Hussain, N. H. (2012). An inquiry-based simulation-supported approach to assist students’ learning of basic electric circuits [Doctoral dissertation, Universiti Teknologi Malaysia]. Universiti Teknologi Malaysia Institutional Repository. [Google Scholar]
- Issa, W., Al-Naemi, F., Al-Greer, M., & Bashir, I. (2023, August 30–September 1). Review on power electronics curriculums in academia and framework development. 2023 58th International Universities Power Engineering Conference (UPEC) (pp. 1–4), Dublin, Ireland. [Google Scholar]
- Itagi, A. R., & Sushma, V. (2016, December 9–10). Enhanced teaching/learning process in analog electronic circuits with an aid of computer simulation tool. 2016 IEEE 4th International Conference on MOOCs, Innovation and Technology in Education (MITE) (pp. 111–116), Madurai, India. [Google Scholar]
- Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85. [Google Scholar] [CrossRef]
- Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. FT Press. [Google Scholar]
- Kolmos, A., De Graaff, E., & Du, X. (2008). Diversity of PBL: PBL learning principles and models. International Journal of Engineering Education, 24(5), 992–1004. [Google Scholar]
- Magana, A. J., & de Jong, T. (2018). Modeling and simulation practices in engineering education. Computer Applications in Engineering Education, 26(4), 731–738. [Google Scholar] [CrossRef]
- Mannan, M. (2017). Role of MATLAB in engineering education: A review. Journal of Engineering Education Transformations, 30(4), 162–169. [Google Scholar]
- Mladenović, V. (2015, April 16). Contemporary electronics with LTSpice and mathematica. Synthesis 2015-International Scientific Conference of IT and Business-Related Research (pp. 134–138), Belgrade, Serbia. [Google Scholar]
- Mohindru, P., & Mohindru, P. (2021). Electronic circuit analysis using LTSPICE XVII simulator: A practical guide for beginners. CRC Press. [Google Scholar]
- Paganotti, L. A., Shope, R., Calhoun, A., & McDonald, P. L. (2024). Barriers and facilitators to implementing simulation-based translational research: A qualitative study. Simulation in Healthcare, 19(4), 220–227. [Google Scholar] [CrossRef]
- Patton, M. Q. (1999). Enhancing the quality and credibility of qualitative analysis. Health Services Research, 34(5 Pt 2), 1189. [Google Scholar]
- Piaget, J. (1985). The equilibration of cognitive structures: The central problem of intellectual development. University of Chicago Press. [Google Scholar]
- Pouncey, J. C., & Lehr, J. M. (2015, May 31–June 4). A spark gap model for LTspice and similar circuit simulation software. 2015 IEEE Pulsed Power Conference (PPC) (pp. 1–6), Austin, TX, USA. [Google Scholar]
- Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231. [Google Scholar] [CrossRef]
- Ptak, P. (2021). Simulation programs in distance learning. In Society. Integration. Education. Proceedings of the International scientific conference (Vol. 5, pp. 436–447). Rezekne Academy of Technologies. [Google Scholar]
- Ramberg, R., & Karlgren, K. (1998). Fostering superficial learning. Journal of Computer Assisted Learning, 14(2), 120–129. [Google Scholar] [CrossRef]
- Rashid, M. H. (2024). SPICE and LTspice for power electronics and electric power. CRC Press. [Google Scholar]
- Rivera-Reyes, P., Lawanto, O., & Pate, M. L. (2017). Students’ assignment interpretation and conceptual understanding in an electronics laboratory. IEEE Transactions on Education, 60(4), 265–272. [Google Scholar] [CrossRef]
- Salovirta, N. (2024). Simulations in electrical engineering education: Simulator development [Master’s thesis, Tampere University of Technology]. Available online: https://trepo.tuni.fi/handle/10024/117084 (accessed on 10 July 2025).
- Schön, D. A. (2017). The reflective practitioner: How professionals think in action. Routledge. [Google Scholar]
- Shekh-Abed, A. (2024). Metacognitive self-knowledge and cognitive skills in project-based learning of high school electronics students. European Journal of Engineering Education, 50(1), 214–229. [Google Scholar] [CrossRef]
- Tenzin, D., Utha, K., & Seden, K. (2023). Effectiveness of simulation, hands-on and a combined strategy in enhancing conceptual understanding on electric circuit: A comparative study. Research in Science & Technological Education, 42, 1069–1085. [Google Scholar] [CrossRef]
- Vlachopoulos, D., & Makri, A. (2017). The effect of games and simulations on higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 14, 1–33. [Google Scholar] [CrossRef]
- Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. [Google Scholar]
- Wang, Y., Ong, S. K., & Nee, A. Y. C. (2018). Enhancing mechanisms education through interaction with augmented reality simulation. Computer Applications in Engineering Education, 26(5), 1552–1564. [Google Scholar] [CrossRef]
- Yin, R. K. (2009). Case study research: Design and methods (Vol. 5). Sage Publications. [Google Scholar]
- Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. [Google Scholar] [CrossRef]
RQ Focus | Theme ID | Thematic Label | Reflection Example | Reflection Count (%) |
---|---|---|---|---|
RQ1: Conceptual Understanding | T1 | Theory–Practice Link | “Simulating the SAR update step-by-step helped me understand how digital conversion works.” | 54 (40%) |
RQ2: Problem-Solving | T2 | Iterative Strategy | “We adjusted Vref in steps, observed errors, and found the optimal range for our ADC.” | 39 (29%) |
RQ2: Problem-Solving | T3 | Metacognitive Awareness | “I learned to explain where I got stuck, and what I would do differently next time.” | 29 (21%) |
RQ3: Engagement | T4 | Peer Learning and Engagement | “A teammate’s explanation helped me debug the circuit. We solved it together.” | 14 (10%) |
Q4: Implementation Challenges | T5 | Integration Reflections | “The project was hard at first, but LTspice made debugging easier and showed me how real circuits behave.” | 25 (18%) |
Theme ID | Reflections (freq.) | Instructor Note | Project Presentation (Exam) | Convergence Level |
---|---|---|---|---|
T1 | 59 (40%) | 12 researcher observations of students connecting theoretical ADC principles with simulation outcomes | 19 out of 25 project teams included labeled waveform plots showing stepwise ADC output behavior | High |
T2 | 39 (29%) | 7 notes on resimulation and problem iterations | 13 out of 25 teams discussed parameter tuning or simulation-debug iterations | High |
T3 | 29 (21%) | 4 instances of self-explanation of errors | 8 out of 25 teams added slides reflecting on how they overcame design challenges or learned from mistakes | Medium |
T4 | 14 (10%) | 2 peer-teaching observations | 3 out of 25 teams shared strategies in final report or slides | Low |
T5 | 25 (18%) | 5 notes on student frustration turning into insight | 6 project teams discussed LTspice as helpful for integration work | Medium |
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Shekh-Abed, A. Enhancing Learning in Microelectronic Circuits: Integrating LTspice Simulations and Structured Reflections in a Design Project. Educ. Sci. 2025, 15, 1045. https://doi.org/10.3390/educsci15081045
Shekh-Abed A. Enhancing Learning in Microelectronic Circuits: Integrating LTspice Simulations and Structured Reflections in a Design Project. Education Sciences. 2025; 15(8):1045. https://doi.org/10.3390/educsci15081045
Chicago/Turabian StyleShekh-Abed, Aziz. 2025. "Enhancing Learning in Microelectronic Circuits: Integrating LTspice Simulations and Structured Reflections in a Design Project" Education Sciences 15, no. 8: 1045. https://doi.org/10.3390/educsci15081045
APA StyleShekh-Abed, A. (2025). Enhancing Learning in Microelectronic Circuits: Integrating LTspice Simulations and Structured Reflections in a Design Project. Education Sciences, 15(8), 1045. https://doi.org/10.3390/educsci15081045