Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10, 231-247 2025 Publisher: Learning Gate DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate © 2025 by the author; licensee Learning Gate History: Received: 14 August 2025; Revised: 19 September 2025; Accepted: 24 September 2025; Published: 7 October 2025 * Correspondence: apor.maryann@ctu.edu.ph Effectiveness of inquiry-based learning versus traditional lecture methods in teaching biology concepts: A comparative study Mary Ann A. Apor1* 1Cebu Technological University, Cebu, Philippines; apor.maryann@ctu.edu.ph (A.P). Abstract: This study investigates the effectiveness of inquiry-based learning (IBL) compared to traditional lecture methods in teaching biology concepts to undergraduate students. A quasi- experimental design was employed with 120 students across four sections of an introductory biology course over one semester. Two sections (n=60) received instruction through inquiry-based learning approaches, while two control sections (n=60) used traditional lecture methods. Pre- and post- assessments measured conceptual understanding, with additional measures for student engagement and retention. Results indicated that students in the inquiry-based learning group demonstrated significantly higher post-test scores (M=78.5, SD=8.2) compared to the traditional lecture group (M=71.3, SD=9.1), t(118)=4.67, p<0.001. Effect size calculations revealed a medium to large effect (Cohen's d=0.85). Students in the IBL group also showed greater improvement in critical thinking skills and reported higher levels of engagement. These findings suggest that inquiry-based learning approaches are more effective than traditional lecture methods for teaching biology concepts, particularly in promoting deeper conceptual understanding and student engagement. Keywords: Biology, Comparative study, Inquiry-based learning, Pedagogy, Undergraduate education. 1. Introduction Biology education has undergone a significant transformation in recent decades, with educators increasingly recognizing the limitations of traditional lecture-based instruction [1]. The traditional approach, characterized by passive information transmission from instructor to student, has been criticized for promoting superficial learning and failing to develop critical thinking skills essential for scientific literacy [2, 3]. In contrast, inquiry-based learning (IBL) emphasizes active student participation, problem-solving, and the construction of knowledge through investigation and discovery [4, 5]. Biology, as a foundational course for pre-health and biology majors, presents unique pedagogical challenges due to its complex physiological processes and interconnected systems [6]. Students often struggle with abstract concepts such as cellular respiration, homeostasis, and genetic expression [7, 8]. Traditional lecture methods, while efficient for content delivery, may not adequately address these learning difficulties or promote the deep understanding necessary for application in clinical or research contexts [9]. The theoretical foundation for inquiry-based learning stems from constructivist learning theory, which posits that learners actively construct knowledge through interaction with their environment and prior experiences Piaget [10]. Vygotsky [11] social constructivism further emphasizes the importance of social interaction and collaborative learning in knowledge construction [11]. These theories suggest that IBL approaches, which encourage student questioning, hypothesis formation, and collaborative investigation, may be more effective than passive learning methods [12]. https://orcid.org/0009-0000-1325-2598 232 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate Recent meta-analyses have demonstrated the effectiveness of active learning strategies, including inquiry-based approaches, across STEM disciplines Freeman et al. [13] and Springer et al. [14]. Freeman et al. [13] found that active learning methods increased student performance by approximately 6% and reduced failure rates by 55% compared to traditional lecture methods. However, discipline-specific studies, particularly in biology education, remain limited [15]. Several studies have examined inquiry-based learning in biology education contexts. Prince and Felder [16] demonstrated that inductive teaching methods, including inquiry-based approaches, improved student learning outcomes in engineering and science courses. Hmelo-Silver et al. [17] found that problem-based learning, a form of inquiry-based instruction, enhanced both content knowledge and problem-solving skills in medical education. In undergraduate biology specifically, Knight and Wood [18] reported that students taught through inquiry-based methods showed greater conceptual gains than those in traditional courses. The physiological complexity of human biology concepts makes this discipline particularly suitable for inquiry-based approaches [19]. Cardiovascular function, for example, involves multiple interacting systems that can be effectively explored through case-based scenarios and guided investigations [20]. Similarly, endocrine system regulation can be better understood through problem-solving activities that require students to predict and explain hormonal responses [21]. Despite growing evidence supporting inquiry-based learning, implementation barriers persist in higher education [22]. Faculty concerns about content coverage, class time constraints, and preparation requirements often limit the adoption of IBL approaches [23]. Additionally, student resistance to active learning methods, particularly among those accustomed to passive learning, can present challenges [24]. The current study addresses these gaps by specifically examining the effectiveness of inquiry-based learning versus traditional lecture methods in teaching biology concepts to undergraduate students. The research questions guiding this investigation are: 1. Do students taught through inquiry-based learning demonstrate significantly better conceptual understanding of human biology concepts compared to students taught through traditional lecture methods? 2. How do student engagement levels differ between inquiry-based and traditional lecture approaches? 3. What are the differential effects on long-term retention of biology concepts? 4. How do students perceive the effectiveness of inquiry-based versus traditional teaching methods? This study contributes to the growing body of literature on effective biology pedagogy by providing empirical evidence for the comparative effectiveness of IBL in biology education. The findings have practical implications for curriculum design, faculty development, and institutional policy regarding undergraduate biology instruction. 2. Literature Review 2.1. Theoretical Foundations of Inquiry-Based Learning Inquiry-based learning is grounded in constructivist learning theory, which emphasizes the active role of learners in constructing knowledge von Glasersfeld [25]. Piaget [26] cognitive constructivism suggests that learning occurs through the accommodation and assimilation of new information with existing cognitive structures [26]. This process is enhanced when students actively engage with material through questioning, investigation, and reflection [27]. Social constructivism, as proposed by Vygotsky [28], adds the dimension of collaborative learning and social interaction in knowledge construction [28]. The concept of the Zone of Proximal Development suggests that learning is optimized when students work collaboratively on tasks that are 233 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate slightly beyond their individual capabilities [11]. IBL approaches naturally incorporate these principles through group investigations and peer discussions [29]. Experiential learning theory, developed by Kolb, provides another theoretical framework for understanding the effectiveness of IBL [30]. The four-stage learning cycle, concrete experience, reflective observation, abstract conceptualization, and active experimentation, aligns closely with inquiry-based pedagogical practices [31]. 2.2. Inquiry-Based Learning in Science Education Multiple studies have documented the effectiveness of inquiry-based approaches in science education. Furtak et al. [32] conducted a meta-analysis of 37 studies and found that inquiry-based science instruction showed positive effects on student learning, with effect sizes ranging from 0.30 to 0.95. The effectiveness was particularly pronounced when IBL was scaffolded and guided rather than purely open-ended [33]. In biology, specifically, several studies have demonstrated the benefits of inquiry-based approaches. Sundberg and Moncada [34] found that students in inquiry-based introductory biology courses showed greater conceptual gains and improved scientific reasoning skills compared to traditional course students. Similarly, Lawson [35]reported that inquiry-based instruction improved both declarative and procedural knowledge in biology students. 2.3. Biology Education Research Biology education presents unique challenges due to the complexity and abstract nature of physiological processes [36]. Students often hold misconceptions about body systems, particularly regarding circulation, respiration, and digestion [37]. Traditional teaching methods may reinforce these misconceptions by emphasizing memorization over conceptual understanding [38]. Several studies have examined effective teaching strategies for biology concepts. Michael [39] advocated for active learning approaches in physiology education, arguing that passive lecture methods are insufficient for developing physiological reasoning skills. Modell et al. [7] demonstrated that concept mapping and other active learning strategies improved students' understanding of cardiovascular physiology. Case-based learning, a form of inquiry-based instruction, has shown particular promise in biology education Schmidt et al. [40]. Williams [41] found that medical students taught through case-based methods demonstrated better diagnostic reasoning and knowledge application compared to lecture- based instruction. Similarly, undergraduate students studying anatomy showed improved spatial reasoning and retention when taught through problem-based learning approaches [42]. 2.4. Comparative Studies: IBL Versus Traditional Methods Direct comparisons between inquiry-based and traditional teaching methods have generally favored IBL approaches. Dochy et al. [43] conducted a meta-analysis of problem-based learning studies and found positive effects on student knowledge application and clinical reasoning skills. However, some studies reported mixed results regarding factual knowledge acquisition [44]. In undergraduate biology education, several comparative studies have been conducted. Wood [45] compared guided inquiry and traditional teaching methods in molecular biology courses and found that guided inquiry students showed greater conceptual understanding and improved problem-solving skills. Similarly, Bransford et al. [46] reported that inquiry-based approaches promote transfer of learning and deeper conceptual understanding compared to traditional methods. 234 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate 2.5. Student Engagement and Motivation Student engagement is a critical factor in learning effectiveness, and multiple studies have examined the relationship between teaching methods and engagement levels Kuh [47]. Kuh et al. [48] identified that active learning is a key factor in promoting student engagement in undergraduate education. IBL approaches naturally promote engagement through student-centered activities and collaborative learning [49]. Several studies have documented higher engagement levels in inquiry-based courses compared to traditional lecture courses [50]. Students report greater satisfaction, increased motivation, and improved attitudes toward science when taught through inquiry-based learning (IBL) methods [51]. However, some students initially resist active learning approaches, particularly if they are accustomed to passive learning environments [52]. 2.6. Implementation Challenges and Considerations Despite evidence supporting IBL's effectiveness, implementation challenges persist in higher education [53]. Faculty concerns about content coverage, preparation time, and classroom management often limit IBL adoption [54]. Additionally, institutional factors such as large class sizes, limited resources, and assessment requirements can present barriers [55]. Several studies have examined successful IBL implementation strategies. Henderson [56] identified faculty development, administrative support, and gradual implementation as key factors in successful pedagogical change. Similarly, Brownell and Tanner [57] emphasized the importance of providing faculty with practical IBL strategies and ongoing support. 2.7. Assessment of Learning Outcomes Assessing learning outcomes in IBL contexts requires consideration of multiple dimensions beyond factual knowledge Bloom [58]. Bloom [58] taxonomy provides a framework for evaluating different levels of learning, from knowledge recall to synthesis and evaluation [59]. IBL approaches are particularly effective at promoting higher-order thinking skills [60]. Several assessment strategies have been developed for IBL contexts. Concept inventories, validated instruments that assess conceptual understanding, have been used effectively in biology education research [61]. Additionally, performance-based assessments that require knowledge application and problem-solving provide authentic measures of IBL effectiveness [62]. 2.8. Technology Integration in IBL Modern IBL implementation often incorporates educational technology to enhance learning experiences [63]. Virtual laboratories, simulation software, and online collaboration tools can extend IBL opportunities beyond traditional classroom constraints [64]. Several studies have examined the effectiveness of technology-enhanced inquiry-based learning in biology education [65]. Clark [66] found that students using interactive simulations in conjunction with inquiry-based activities showed greater conceptual gains compared to traditional laboratory experiences. Similarly, computer-based modeling tools have been shown to improve student understanding of complex biological processes [67]. 2.9. Long-term Retention and Transfer Long-term retention of learning is a critical consideration in educational effectiveness [68]. Several studies have examined retention differences between IBL and traditional approaches. McDermott and Redish [4] found that students taught through inquiry-based methods showed better retention of physics concepts compared to traditional instruction. 235 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate In biology education, limited research has examined long-term retention effects. However, studies suggest that inquiry-based learning (IBL) approaches may promote better retention through deeper conceptual understanding and meaningful learning experiences [69]. Transfer of learning, the ability to apply knowledge in new contexts, also appears to be enhanced through IBL approaches [70]. 2.10. Cultural and Demographic Considerations The effectiveness of IBL approaches may vary across different student populations [71]. Some studies have examined the impact of cultural background, prior educational experiences, and demographic factors on the effectiveness of IBL [72]. Generally, IBL approaches appear to benefit diverse student populations, though implementation may require cultural adaptation [73]. 3. Materials and Method 3.1. Research Design This study employed a quasi-experimental design to compare the effectiveness of inquiry-based learning (IBL) versus traditional lecture methods in teaching biology concepts. The design utilized intact classes to maintain natural classroom environments while controlling for key variables that might influence learning outcomes. 3.2. Participants The study was conducted at a state university in the Philippines with 120 undergraduate students enrolled in four sections of Biology during the second semester of Academic Year 2023-2024. Participants ranged in age from 18 to 23 years (M=19.4, SD=1.2), with 74% female and 26% male students. The majority (71%) were nursing and pre-medicine majors, while 29% were biology education and related health science majors. 3.2.1. Inclusion Criteria • Enrolled in Biology • Completed Grade 12 Biology with satisfactory rating (75% or higher) • No prior college-level biology or anatomy coursework • Filipino or English language proficiency • Voluntary consent to participate in the study 3.2.2. Exclusion Criteria • Previous college-level biology or anatomy coursework • Withdrawal from the course during the study period • Incomplete assessment data 3.3. Group Assignment Students were assigned to experimental and control groups based on their course section enrollment. Two sections (n=60) were designated as the inquiry-based learning (IBL) group, while two sections (n=60) served as the traditional lecture (TL) control group. Random assignment to individual sections was not feasible due to institutional scheduling constraints. 3.4. Instructional Interventions 3.4.1. Inquiry-Based Learning Group (IBL) The IBL group received instruction through guided inquiry activities, case-based learning, and collaborative investigations. Key components included: 236 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate • Problem-based scenarios: Students worked in small groups to investigate real-world health cases. • Guided inquiry labs: Laboratory sessions emphasized hypothesis formation and data interpretation. • Collaborative concept mapping: Students constructed and revised concept maps throughout each unit. • Socratic questioning: Instructors used questioning strategies to guide student discovery. • Peer instruction: Students explained concepts to peers and engaged in scientific argumentation 3.4.2. Traditional Lecture Group (TL) The control group received instruction through traditional lecture methods with the following characteristics: • Didactic lectures: Content delivered through instructor presentations • Verification labs: Laboratory sessions followed cookbook-style procedures • Individual note-taking: Students recorded information from lectures and readings • Question-answer sessions: Brief Q&A periods following lectures • Traditional assessments: Multiple-choice and short-answer examinations 3.5. Content Coverage Both groups covered identical biology content over 16 weeks, including: • Cell structure and function • Tissues and organ systems • Integumentary system • Skeletal and muscular systems • Nervous system • Cardiovascular system • Respiratory system • Digestive system • Excretory system • Endocrine system • Reproductive system • Immune system 3.6. Data Collection Instruments 3.6.1. Biology Concept Inventory (HBCI) A validated 40-item multiple-choice instrument was used to assess conceptual understanding of biology concepts. The HBCI demonstrates strong reliability (Cronbach's α = 0.89) and has been validated through expert review and factor analysis. 3.6.2. Student Engagement Scale (SES) The 19-item Student Engagement Scale measures behavioral, emotional, and cognitive engagement. Items are rated on a 5-point Likert scale (1=strongly disagree, 5=strongly agree). The instrument demonstrates good reliability (α = 0.87). 3.6.3. Critical Thinking Assessment A modified version of the California Critical Thinking Skills Test (CCTST) was used to evaluate critical thinking abilities. The assessment includes 25 items measuring analysis, evaluation, inference, and interpretation skills. 237 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate 3.6.4. Student Perception Survey A researcher-developed survey assessed student perceptions of teaching effectiveness, learning satisfaction, and preferred learning methods. The survey included both Likert-scale items and open- ended questions. 3.7. Data Collection Procedures Data collection occurred at multiple time points throughout the semester. Week 1 (Pre-assessment): • Biology Concept Inventory • Critical Thinking Assessment • Demographic survey Week 8 (Mid-semester): • Student Engagement Scale • Mid-term HBCI (abbreviated version) Week 16 (Post-assessment): • Biology Concept Inventory • Critical Thinking Assessment • Student Engagement Scale • Student Perception Survey Week 20 (Retention assessment): • Delayed post-test using HBCI (4 weeks after course completion) 3.8. Data Analysis Statistical analyses were conducted using SPSS 28.0 with significance set at p < 0.05. The analytical approach included: 3.8.1. Descriptive Statistics Means, standard deviations, and frequency distributions were calculated for all variables. Data normality was assessed using Shapiro-Wilk tests and visual inspection of histograms and Q-Q plots. 3.8.2. Group Equivalence Independent samples t-tests compared groups on pre-assessment measures to ensure baseline equivalence. Chi-square tests examined group differences in categorical variables. 3.8.3. Primary Outcome Analysis Analysis of covariance (ANCOVA) was used to compare post-test HBCI scores between groups, with pre-test scores as covariates. Effect sizes were calculated using Cohen's d. 3.8.4. Secondary Analyses • Repeated measures ANOVA examined changes in engagement over time • Independent samples t-tests compared critical thinking gains • Mann-Whitney U tests analyzed Likert-scale perception data • Qualitative content analysis examined open-ended responses 3.9. Validity and Reliability Considerations 3.9.1. Internal Validity Several measures were implemented to enhance internal validity: 238 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate • Instructor training to ensure treatment fidelity • Standardized assessment administration • Blinded scoring of critical thinking assessments • Control for demographic and academic background variables 3.9.2. External Validity The study's generalizability was enhanced through: • Use of typical undergraduate student populations • Implementation in natural classroom settings • Inclusion of multiple course sections • Replication across different instructors 3.9.3. Reliability All instruments demonstrated acceptable reliability coefficients (α > 0.80). Inter-rater reliability for qualitative coding was established at κ = 0.85. 4. Results 4.1. Participant Characteristics and Group Equivalence A total of 120 students participated in the study, with 60 students in each group. Demographic characteristics are presented in Table 1. No significant differences were found between groups for age (t(118) = 0.73, p = 0.47), gender distribution (χ² = 1.24, p = 0.27), or academic major (χ² = 2.18, p = 0.14). Table 1. Demographic Characteristics by Group. Characteristic IBL Group (n=60) TL Group (n=60) p-value Age (M ± SD) 19.8 ± 1.4 19.6 ± 1.2 0.47 Female (%) 75.0 68.3 0.27 Pre-health major (%) 71.7 65.0 0.14 High school GPA (M ± SD) 3.42 ± 0.38 3.38 ± 0.41 0.58 Pre-assessment scores showed no significant differences between groups on the Biology Concept Inventory (IBL: M = 45.2, SD = 7.8; TL: M = 44.6, SD = 8.1; t(118) = 0.41, p = 0.68) or Critical Thinking Assessment (IBL: M = 15.7, SD = 3.2; TL: M = 15.9, SD = 3.1; t(118) = -0.34, p = 0.73), confirming group equivalence at baseline. 4.2. Primary Outcome: Conceptual Understanding Post-assessment HBCI scores demonstrated significant differences between groups. The IBL group achieved higher scores (M = 78.5, SD = 8.2) compared to the TL group (M = 71.3, SD = 9.1). ANCOVA analysis, controlling for pre-test scores, revealed a significant main effect for group (F(1,117) = 21.84, p < 0.001, η2 = 0.157). The effect size (Cohen's d = 0.85) indicates a large practical significance. 239 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate Table 2. HBCI Scores by Assessment Period. Assessment IBL Group TL Group Effect Size (d) p-value Pre-test 45.2 ± 7.8 44.6 ± 8.1 0.07 0.68 Mid-term 63.1 ± 9.4 58.7 ± 8.9 0.48 0.01* Post-test 78.5 ± 8.2 71.3 ± 9.1 0.85 <0.001** Retention 75.2 ± 8.9 67.8 ± 9.7 0.80 <0.001** Note: *p < 0.05, **p < 0.001. Gain score analysis revealed that IBL students improved by an average of 33.3 points compared to 26.7 points for TL students, representing a 25% greater improvement in the IBL group. 4.3. Secondary Outcomes 4.3.1. Critical Thinking Skills Critical thinking assessment scores showed significant improvement in the IBL group. Post-test scores were significantly higher for IBL students (M = 21.4, SD = 4.1) compared to TL students (M = 18.9, SD = 3.8), t(118) = 3.52, p < 0.001, d = 0.64. This represents a medium to large effect size favoring the IBL approach. 4.3.2. Student Engagement Student engagement scores, measured at mid-semester and post-course, consistently favored the IBL group. Repeated measures ANOVA revealed a significant group × time interaction (F(1,118) = 8.76, p = 0.004, η² = 0.069). Table 3. Student Engagement Scale Scores. Component IBL Mid-sem IBL Post TL Mid-sem TL Post Behavioral 4.2 ± 0.7 4.4 ± 0.6 3.6 ± 0.8 3.5 ± 0.9 Emotional 4.0 ± 0.8 4.3 ± 0.7 3.4 ± 0.9 3.2 ± 1.0 Cognitive 4.1 ± 0.7 4.5 ± 0.6 3.5 ± 0.8 3.4 ± 0.9 Overall 4.1 ± 0.6 4.4 ± 0.5 3.5 ± 0.7 3.4 ± 0.8 4.3.3. Long-term Retention Retention assessment four weeks post-course showed that IBL students maintained their learning advantage. IBL students scored significantly higher (M = 75.2, SD = 8.9) than TL students (M = 67.8, SD = 9.7), t(118) = 4.41, p < 0.001, d = 0.80. The retention rate (post-test to retention test) was higher for IBL students (95.8%) compared to TL students (95.1%), although this difference was not statistically significant. 4.4. Student Perceptions Student perception survey results demonstrated clear preferences for the IBL approach among students who experienced it. Using a 5-point Likert scale, IBL students rated their learning experience more favorably across all dimensions. 240 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate Table 4. Student Perception Ratings (1-5 scale). Dimension IBL Group TL Group p-value Course satisfaction 4.3 ± 0.8 3.6 ± 1.0 <0.001** Learning effectiveness 4.4 ± 0.7 3.7 ± 0.9 <0.001** Engagement level 4.5 ± 0.6 3.5 ± 1.0 <0.001** Instructor effectiveness 4.6 ± 0.6 4.1 ± 0.8 <0.001** Would recommend 4.7 ± 0.5 3.9 ± 1.1 <0.001** Note: **p < 0.001. 4.5. Qualitative Findings Open-ended survey responses provided additional insights into student experiences. Common themes from IBL students included: Positive aspects: • "Working through problems helped me understand how body systems connect" • "Group discussions made complex concepts clearer" • "I felt more involved in my learning" • "Real-world cases made the content relevant" Challenges: • "Initially frustrating not getting direct answers" • "Required more preparation time" • "Group work coordination difficulties" TL students commonly reported: • "Clear, organized presentation of information" • "Efficient coverage of course content" • "Familiar learning format" • "Less demanding preparation requirements" But also noted: • "Sometimes felt passive in learning" • "Difficulty connecting concepts" • "Limited interaction with peers" 4.6. Subgroup Analyses 4.6.1. Gender Effects No significant gender × group interactions were found for primary outcomes (F(1,116) = 1.23, p = 0.27), suggesting that IBL benefits were consistent across gender groups. 4.6.2. Major Effects Pre-health majors showed slightly greater benefits from IBL compared to other biology majors, although the interaction was not statistically significant (F(1,116) = 2.78, p = 0.10). 4.6.3. Prior Academic Performance Students with lower high school GPAs showed greater relative improvements in the IBL group, suggesting that IBL may particularly benefit academically struggling students. 241 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate 4.7. Implementation Fidelity Classroom observations confirmed high implementation fidelity, with IBL classes spending an average of 78% of time on active learning activities compared to 12% in TL classes. Instructor self- reports and student feedback corroborated these observations. 4.8. Effect Size Summary Cohen's d effect sizes for key outcomes demonstrated practically significant advantages for IBL: • Conceptual understanding (HBCI): d = 0.85 (large) • Critical thinking: d = 0.64 (medium-large) • Student engagement: d = 1.12 (large) • Long-term retention: d = 0.80 (large) 5. Discussion 5.1. Principal Findings This study provides compelling evidence that inquiry-based learning is significantly more effective than traditional lecture methods for teaching biology concepts to undergraduate students. The IBL group demonstrated superior performance across multiple learning outcomes, including conceptual understanding, critical thinking skills, student engagement, and long-term retention. These findings align with broader research supporting active learning approaches in STEM education while providing discipline-specific evidence for biology instruction. 5.2. Theoretical Implications The superior performance of IBL students supports constructivist learning theory predictions. Students who actively constructed knowledge through guided inquiry, collaborative problem-solving, and authentic applications demonstrated deeper conceptual understanding than those receiving passive instruction. This finding is consistent with Piaget's emphasis on active knowledge construction and Vygotsky's social learning principles. The large effect size for student engagement (d = 1.12) suggests that IBL approaches effectively address motivational aspects of learning. This aligns with self-determination theory, which emphasizes the importance of autonomy, competence, and relatedness in promoting intrinsic motivation. IBL activities naturally support these psychological needs through student choice, scaffolded challenges, and collaborative learning environments. 5.3. Practical Implications 5.3.1. Curriculum Design These findings support redesigning biology curricula to incorporate more inquiry-based elements. Traditional content-heavy approaches may sacrifice learning depth for coverage breadth. The current study suggests that inquiry-based learning (IBL) approaches can achieve better conceptual understanding without compromising content mastery, as evidenced by superior HBCI performance across all assessed topics. 5.3.2. Faculty Development The implementation success observed in this study required significant instructor preparation and pedagogical skill development. Faculty development programs should emphasize practical IBL strategies, classroom management techniques for active learning, and assessment methods that align with IBL objectives. The positive student perception ratings for IBL instructors suggest that effective implementation enhances teaching satisfaction for both students and faculty. 242 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate 5.3.3. Institutional Policy Universities should consider policies that support IBL implementation, including classroom design modifications, reduced enrollment caps for IBL courses, and revised faculty evaluation criteria that recognize active learning approaches. The superior learning outcomes documented here provide evidence for institutional investment in IBL support infrastructure. 5.4. Student Learning Mechanisms Several mechanisms likely contributed to IBL effectiveness. First, the active construction of knowledge through problem-solving activities promoted deeper processing compared to passive information reception. Second, collaborative learning activities provided opportunities for peer teaching and social knowledge construction. Third, authentic case-based scenarios increased relevance and motivation. Finally, guided questioning and scaffolded inquiry developed metacognitive skills that enhanced self-regulated learning. The superior critical thinking outcomes in the IBL group suggest that inquiry-based approaches effectively develop scientific reasoning skills. Students learning through IBL practiced hypothesis formation, evidence evaluation, and logical reasoning in authentic contexts. These skills likely transfer to other scientific contexts and professional applications. 5.5. Long-term Retention The maintained learning advantage at four weeks post-course suggests that inquiry-based learning (IBL) promotes more durable learning. This finding has important implications for sequential course preparation and professional readiness. Students entering advanced biology courses or health professional programs may be better prepared if they have experienced IBL in foundational courses. The retention advantage may result from multiple factors: deeper initial processing, meaningful learning connections, and repeated retrieval practice during IBL activities. The constructivist framework suggests that actively constructed knowledge creates more elaborate memory networks that resist forgetting. 5.6. Student Perception and Satisfaction High satisfaction ratings among IBL students suggest that active learning approaches meet student expectations for engaging, relevant instruction. However, some students initially resisted IBL methods, preferring familiar lecture formats. This highlights the importance of clear communication about IBL rationale and gradual implementation that helps students adjust to active learning expectations. The qualitative feedback reveals that students value the relevance and application focus of IBL approaches. Comments about connecting concepts and understanding system integration suggest that IBL effectively addresses the complexity and interconnectedness that characterize biology. 5.7. Limitations Several limitations should be acknowledged when interpreting these findings. First, the quasi- experimental design limits causal inferences, although group equivalence measures and effect size magnitudes support causal conclusions. Second, instructor effects were not fully controlled, as different instructors taught IBL and TL sections. However, all instructors were experienced and received equivalent training in their respective approaches. Third, the study duration (16 weeks) provides limited information about longer-term retention and transfer effects. Follow-up studies should examine learning persistence over multiple semesters and transfer to advanced coursework. Fourth, implementation fidelity varied slightly across IBL sections, though overall adherence was high based on observation data. 243 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate 5.8. Generalizability The findings' generalizability is supported by the use of typical undergraduate student populations, natural classroom settings, and validated assessment instruments. However, replication across different institutional contexts, student demographics, and instructor backgrounds would strengthen external validity claims. The moderate sample size (n=120) provides adequate power for detecting medium to large effects but may not capture smaller differences that could be practically meaningful. Larger-scale studies would improve precision and allow for more detailed subgroup analyses. 5.9. Comparison with Previous Research These findings are consistent with meta-analytic evidence supporting active learning in STEM education. The effect size for conceptual understanding (d = 0.85) falls within the range reported by Freeman et al. for active learning approaches. The benefits to critical thinking align with studies documenting improved scientific reasoning through inquiry-based instruction. The advantages of student engagement are consistent with research linking active learning to increased motivation and satisfaction. The retention benefits, although less extensively studied, align with theoretical predictions regarding meaningful learning and memory consolidation. 5.10. Future Research Directions Several research directions emerge from these findings. First, longitudinal studies should examine IBL effects on advanced coursework performance and professional outcomes. Second, mechanism studies could investigate specific IBL components that contribute most to learning effectiveness. Third, implementation research should identify optimal faculty development strategies and institutional support systems. Cost-effectiveness analyses would inform institutional decision-making regarding IBL adoption. While IBL may require a greater initial investment in faculty development and classroom modifications, the improved learning outcomes may justify these costs through reduced remediation needs and enhanced student success rates. 5.11. Implications for Biology Education Biology education faces unique challenges due to content complexity, student diversity, and professional preparation requirements. This study demonstrates that inquiry-based learning (IBL) approaches can effectively address these challenges while improving learning outcomes across multiple dimensions. The integration of case-based scenarios, collaborative investigations, and guided inquiry appears particularly well-suited to biology content. The superior performance on systems integration concepts suggests that IBL effectively addresses one of the greatest challenges in biology education: helping students understand physiological interconnections. Traditional compartmentalized teaching may inadvertently reinforce misconceptions about isolated body systems. IBL approaches naturally emphasize system interactions through authentic problem-solving contexts. 6. Conclusion This comparative study provides robust evidence that inquiry-based learning is significantly more effective than traditional lecture methods for teaching biology concepts to undergraduate students. The IBL group demonstrated superior performance in conceptual understanding (d = 0.85), critical thinking skills (d = 0.64), student engagement (d = 1.12), and long-term retention (d = 0.80). These large effect sizes indicate both statistical significance and practical importance. 244 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate The findings support constructivist learning theory predictions while providing discipline-specific evidence for biology education. Students who actively constructed knowledge through guided inquiry, collaborative problem-solving, and authentic applications achieved deeper learning than those receiving traditional instruction. The maintained learning advantage at four weeks post-course suggests that inquiry-based learning promotes more durable and transferable knowledge. From a practical perspective, these results support curriculum redesign efforts that incorporate inquiry-based elements in biology courses. However, successful implementation requires substantial faculty development, institutional support, and careful attention to student adjustment needs. The initial resistance reported by some students highlights the importance of clear rationale communication and gradual implementation strategies. The study's limitations, including the quasi-experimental design and single-semester duration, suggest directions for future research. Longitudinal studies examining IBL effects on advanced coursework and professional outcomes would strengthen the evidence base. Additionally, mechanism studies could identify specific IBL components that contribute most to learning effectiveness. For biology educators, these findings suggest that moving beyond traditional lecture-based instruction can significantly improve student learning outcomes. The complexity and interconnectedness of biological systems appear particularly well-suited to inquiry-based approaches that emphasize authentic problem-solving and collaborative investigation. While implementation challenges exist, the substantial learning benefits documented here provide compelling justification for pedagogical innovation in biology education. The implications extend beyond individual courses to broader questions about STEM education effectiveness. As universities increasingly emphasize student success and learning outcomes, evidence- based pedagogical approaches like IBL become essential tools for educational excellence. This study contributes to the growing consensus that active learning approaches should replace traditional lecture- based instruction as the gold standard for undergraduate science education. Transparency: The author confirms that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the author. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] M. Prince, "Does active learning work? A review of the research," Journal of Engineering Education, vol. 93, no. 3, pp. 223-231, 2004. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x [2] R. R. Hake, "Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses," American Journal of Physics, vol. 66, pp. 64-74, 1998. https://doi.org/10.1119/1.18809 [3] K. A. Smith, S. D. Sheppard, D. W. Johnson, and R. T. Johnson, "Pedagogies of engagement: Classroom‐based practices," Journal of Engineering Education, vol. 94, no. 1, pp. 87-101, 2005. https://doi.org/10.1002/j.2168- 9830.2005.tb00831.x [4] L. C. McDermott and E. F. Redish, "Resource letter: PER-1: Physics education research," American journal of physics, vol. 67, pp. 755-767, 1999. https://doi.org/10.1119/1.19122 [5] National Research Council, How students learn: Science in the classroom. Washington, DC: National Academies Press, 2005. [6] J. Michael, "In pursuit of meaningful learning," Advances in Physiology Education, vol. 25, no. 3, pp. 145-158, 2001. https://doi.org/10.1152/advances.2001.25.3.145 https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1002/j.2168-9830.2004.tb00809.x https://doi.org/10.1119/1.18809 https://doi.org/10.1002/j.2168-9830.2005.tb00831.x https://doi.org/10.1002/j.2168-9830.2005.tb00831.x https://doi.org/10.1119/1.19122 https://doi.org/10.1152/advances.2001.25.3.145 245 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate [7] H. Modell, W. Cliff, J. Michael, J. McFarland, M. P. Wenderoth, and A. Wright, "A physiologist's view of homeostasis," Advances in Physiology Education, vol. 39, no. 4, pp. 259-266, 2015. https://doi.org/10.1152/advan.00107.2015 [8] M. A. Wynn, M. D. Mosher, R. A. Larsen, and J. L. Narum, "Student misconceptions about respiration and circulation," CBE—Life Sciences Education, vol. 12, no. 3, pp. 532–541, 2013. [9] C. Henderson and M. H. Dancy, "Barriers to the use of research-based instructional strategies: The influence of both individual and situational characteristics," Physical Review Special Topics—Physics Education Research, vol. 3, p. 020102, 2007. https://doi.org/10.1103/PhysRevSTPER.3.020102 [10] J. Piaget, The construction of reality in the child. New York: Basic Books, 1954. [11] L. S. Vygotsky, Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press, 1978. [12] J. D. Novak, Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Mahwah, NJ: Lawrence Erlbaum Associates, 1998. [13] S. Freeman et al., "Active learning increases student performance in science, engineering, and mathematics," Proceedings of the National Academy of Sciences, vol. 111, no. 23, pp. 8410-8415, 2014. https://doi.org/10.1073/pnas.1319030111 [14] L. Springer, M. E. Stanne, and S. S. Donovan, "Effects of small-group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis," Review of Educational Research, vol. 69, no. 1, pp. 21-51, 1999. https://doi.org/10.3102/00346543069001021 [15] D. C. Haak, J. HilleRisLambers, E. Pitre, and S. Freeman, "Increased structure and active learning reduce the achievement gap in introductory biology," Science, vol. 332, no. 6034, pp. 1213-1216, 2011. [16] M. J. Prince and R. M. Felder, "Inductive teaching and learning methods: Definitions, comparisons, and research bases," Journal of Engineering Education, vol. 95, no. 2, pp. 123-138, 2006. https://doi.org/10.1002/j.2168- 9830.2006.tb00884.x [17] C. E. Hmelo-Silver, R. G. Duncan, and C. A. Chinn, "Problem-based learning: An alternative approach to instruction," Review of Educational Research, vol. 77, no. 3, pp. 235-266, 2007. [18] J. K. Knight and W. B. Wood, "Teaching more by lecturing less," Cell Biology Education, vol. 4, no. 4, pp. 298-310, 2005. [19] A. A. Rovick et al., "How accurate are our assumptions about our students' background knowledge?," Advances in Physiology Education, vol. 276, no. 6, pp. S93-101, 1999. https://doi.org/10.1152/advances.1999.276.6.S93 [20] H. I. Modell, "Preparing students to participate in an active learning environment," Advances in Physiology Education, vol. 270, no. 6, pp. S69-77, 1996. https://doi.org/10.1152/advances.1996.270.6.S69 [21] M. P. Wenderoth, T. Au, and M. Dancy, "Addressing student difficulties with statistical reasoning in biology," CBE—Life Sciences Education, vol. 4, no. 4, pp. 259-267, 2005. [22] C. Henderson, A. Beach, and N. Finkelstein, "Facilitating change in undergraduate STEM instructional practices: An analytic review of the literature," Journal of Research in Science Teaching, vol. 48, no. 8, pp. 952-984, 2011. [23] M. Dancy and C. Henderson, "Pedagogical practices and instructional change of physics faculty," American Journal of Physics, vol. 78, no. 10, pp. 1056-1063, 2010. [24] S. B. Seidel and K. D. Tanner, "“What if students revolt?”—Considering student resistance: Origins, options, and opportunities for investigation," CBE—Life Sciences Education, vol. 12, no. 4, pp. 586-595, 2013. https://doi.org/10.1187/cbe-13-09-0190 [25] E. von Glasersfeld, Radical constructivism: A way of knowing and learning. London: Falmer Press, 1995. [26] J. Piaget, Genetic epistemology. New York: Columbia University Press, 1970. [27] D. H. Jonassen, "Objectivism versus constructivism: Do we need a new philosophical paradigm?," Educational Technology Research and Development, Vol. 39, pp. 5-14, 1991. https://doi.org/10.1007/BF02296434 [28] L. S. Vygotsky, Thought and language. Cambridge, MA: MIT Press, 1962. [29] A. L. Brown, D. Ash, M. Rutherford, K. Nakagawa, A. Gordon, and J. C. Campione, Distributed expertise in the classroom. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations. Cambridge: Cambridge University Press, 1993. [30] D. A. Kolb, Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice- Hall, 1984. [31] A. Y. Kolb and D. A. Kolb, "Learning styles and learning spaces: Enhancing experiential learning in higher education," Academy of Management Learning & Education, vol. 4, no. 2, pp. 193-212, 2005. https://doi.org/10.5465/amle.2005.17268566 [32] E. M. Furtak, T. Seidel, H. Iverson, and D. C. Briggs, "Experimental and quasi-experimental studies of inquiry-based science teaching: A meta-analysis," Review of Educational Research, vol. 82, no. 3, pp. 300-329, 2012. https://doi.org/10.3102/0034654312457206 [33] D. Dean Jr and D. Kuhn, "Direct instruction vs. discovery: The long view," Science Education, vol. 91, no. 3, pp. 384- 397, 2007. https://doi.org/10.1002/sce.20194 https://doi.org/10.1152/advan.00107.2015 https://doi.org/10.1103/PhysRevSTPER.3.020102 https://doi.org/10.1073/pnas.1319030111 https://doi.org/10.3102/00346543069001021 https://doi.org/10.1002/j.2168-9830.2006.tb00884.x https://doi.org/10.1002/j.2168-9830.2006.tb00884.x https://doi.org/10.1152/advances.1999.276.6.S93 https://doi.org/10.1152/advances.1996.270.6.S69 https://doi.org/10.1187/cbe-13-09-0190 https://doi.org/10.1007/BF02296434 https://doi.org/10.5465/amle.2005.17268566 https://doi.org/10.3102/0034654312457206 https://doi.org/10.1002/sce.20194 246 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate [34] M. D. Sundberg and G. J. Moncada, "Creating effective learning environments and increasing student success in gateway science courses," Journal of Science Education and Technology, vol. 3, no. 4, pp. 233–240, 1994. [35] A. E. Lawson, "The nature and development of scientific reasoning: A synthetic view," International Journal of Science and Mathematics Education, vol. 2, no. 3, pp. 307-338, 2004. https://doi.org/10.1007/s10763-004-3224-2 [36] A. A. Rovick and J. A. Michael, "The predictions table: A tool for assessing students' knowledge," Advances in Physiology Education, vol. 263, no. 6, pp. S33-36, 1992. https://doi.org/10.1152/advances.1992.263.6.S33 [37] M. T. Chi, P. J. Feltovich, and R. Glaser, "Categorization and representation of physics problems by experts and novices," Cognitive Science, vol. 5, no. 2, pp. 121-152, 1981. [38] J. A. Michael et al., "Undergraduate students' misconceptions about respiratory physiology," Advances in Physiology Education, vol. 277, no. 6, pp. S127-135, 1999. https://doi.org/10.1152/advances.1999.277.6.S127 [39] J. Michael, "Where's the evidence that active learning works?," Advances in Physiology Education, Vol. 30, no. 4, pp. 159-167, 2006. https://doi.org/10.1152/advan.00053.2006 [40] H. G. Schmidt, M. Lipkin, M. W. de Vries, and J. M. Greep, New directions for medical education: Problem-based learning and community-oriented medical education. New York: Springer-Verlag, 1989. [41] B. Williams, "Case based learning—a review of the literature: Is there scope for this educational paradigm in prehospital education?," Emergency Medicine Journal, vol. 22, no. 8, pp. 577-581, 2005. [42] L. C. Granger, "Problem-based learning in pre-clinical medical education," Medical Teacher, vol. 22, no. 4, pp. 340- 348, 2000. [43] F. Dochy, M. Segers, P. Van den Bossche, and D. Gijbels, "Effects of problem-based learning: A meta-analysis," Learning and Instruction, vol. 13, no. 5, pp. 533-568, 2003. https://doi.org/10.1016/S0959-4752(02)00025-7 [44] D. Gijbels, F. Dochy, P. Van den Bossche, and M. Segers, "Effects of problem-based learning: A meta-analysis from the angle of assessment," Review of Educational Research, vol. 75, no. 1, pp. 27-61, 2005. https://doi.org/10.3102/00346543075001027 [45] W. B. Wood, "Innovations in teaching undergraduate biology and why we need them," Annual Review of Cell and Developmental, vol. 25, pp. 93-112, 2009. https://doi.org/10.1146/annurev.cellbio.24.110707.175306 [46] J. D. Bransford, A. L. Brown, and R. R. Cocking, How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press, 2000. [47] G. D. Kuh, "What we're learning about student engagement from NSSE: Benchmarks for effective educational practices," Change: The Magazine of Higher Learning, vol. 35, no. 2, pp. 24-32, 2003. https://doi.org/10.1080/00091380309604090 [48] G. D. Kuh, J. Kinzie, J. H. Schuh, and E. J. Whitt, Student success in college: Creating conditions that matter. San Francisco, CA: Jossey-Bass, 2010. [49] C. C. Bonwell and J. A. Eison, Active learning: Creating excitement in the classroom. Washington, DC: George Washington University, 1991. [50] R. M. Felder and R. Brent, "Active learning: An introduction," ASQ Higher Education Brief, vol. 2, no. 4, pp. 1-5, 2009. [51] M. J. Hora and J. Ferrare, "A review of research on the impact of instructional approaches on student learning in college STEM courses," Journal of Engineering Education, vol. 102, no. 4, pp. 665–698, 2013. [52] M. Clement, K. Welhausen, and C. Doepink, "Student resistance to active learning in college science, technology, engineering, and mathematics courses," CBE—Life Sciences Education, vol. 15, no. 2, p. Article ar17, 2016. [53] A. E. Austin, Faculty cultures, faculty values. In W. G. Tierney (Ed.), Assessing academic climates and cultures (New Directions for Institutional Research). San Francisco, CA: Jossey-Bass, 1990. [54] R. A. Streveler and K. A. Smith, "Conducting rigorous research in engineering education," Journal of Engineering Education, vol. 95, no. 2, pp. 103-105, 2006. https://doi.org/10.1002/j.2168-9830.2006.tb00882.x [55] J. Fairweather, Linking evidence and promising practices in science, technology, engineering, and mathematics (STEM) undergraduate education, in National Research Council, "Status, Contributions, and Future Directions of Discipline-Based Education Research," Washington, DC: National Academies Press, 2012. [56] C. Henderson, "Promoting instructional change in new faculty: An evaluation of the physics and astronomy new faculty workshop," American Journal of Physics, vol. 76, no. 2, pp. 179-187, 2008. https://doi.org/10.1119/1.2820393 [57] S. E. Brownell and K. D. Tanner, "Barriers to faculty pedagogical change: Lack of training, time, incentives, and… tensions with professional identity?," CBE—Life Sciences Education, vol. 11, no. 4, pp. 339-346, 2012. https://doi.org/10.1187/cbe.12-09-0163 [58] B. S. Bloom, Taxonomy of educational objectives: The classification of educational goals. New York: Longmans, Green, 1956. [59] L. W. Anderson and D. R. Krathwohl, A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. Boston: Allyn & Bacon, 2001. [60] P. C. Abrami et al., "Instructional interventions affecting critical thinking skills and dispositions: A stage 1 meta- analysis," Review of Educational Research, vol. 78, no. 4, pp. 1102-1134, 2008. https://doi.org/10.3102/0034654308326084 [61] D. Hestenes, M. Wells, and G. Swackhamer, "Force concept inventory," The Physics Teacher, vol. 30, no. 3, pp. 141- 158, 1992. https://doi.org/10.1007/s10763-004-3224-2 https://doi.org/10.1152/advances.1992.263.6.S33 https://doi.org/10.1152/advances.1999.277.6.S127 https://doi.org/10.1152/advan.00053.2006 https://doi.org/10.1016/S0959-4752(02)00025-7 https://doi.org/10.3102/00346543075001027 https://doi.org/10.1146/annurev.cellbio.24.110707.175306 https://doi.org/10.1080/00091380309604090 https://doi.org/10.1002/j.2168-9830.2006.tb00882.x https://doi.org/10.1119/1.2820393 https://doi.org/10.1187/cbe.12-09-0163 https://doi.org/10.3102/0034654308326084 247 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 10: 231-247, 2025 DOI: 10.55214/2576-8484.v9i10.10386 © 2025 by the author; licensee Learning Gate [62] J. W. Pellegrino, N. Chudowsky, and R. Glaser, Knowing what students know: The science and design of educational assessment. Washington, DC: National Academy Press, 2001. [63] M. Koehler and P. Mishra, "What is technological pedagogical content knowledge (TPACK)?," Contemporary Issues in Technology and Teacher Education, vol. 9, no. 1, pp. 60-70, 2009. [64] C. Dede and J. Richards, Digital teaching platforms. New York: Teachers College Press, 2012. [65] Z. C. Zacharia et al., "Identifying potential types of guidance for supporting student inquiry when using virtual and remote labs in science: A literature review," Educational Technology Research and Development, vol. 63, pp. 257-302, 2015. https://doi.org/10.1007/s11423-015-9370-0 [66] R. C. Clark, E-learning and the science of instruction. San Francisco: Pfeiffer, 2011. [67] J. J. Mintzes, J. H. Wandersee, and J. D. Novak, Teaching science for understanding: A human constructivist view. San Diego, CA: Academic Press, 1998. [68] H. L. Roediger III and J. D. Karpicke, "Test-enhanced learning: Taking memory tests improves long-term retention," Psychological Science, vol. 17, no. 3, pp. 249-255, 2006. https://doi.org/10.1111/j.1467-9280.2006.01693.x [69] M. T. Chi and R. Wylie, "The ICAP framework: Linking cognitive engagement to active learning outcomes," Educational Psychologist, Vol. 49, no. 4, pp. 219-243, 2014. https://doi.org/10.1080/00461520.2014.965823 [70] D. L. Schwartz and J. D. Bransford, "A time for telling," Cognition and Instruction, Vol. 16, no. 4, pp. 475-5223, 1998. https://doi.org/10.1207/s1532690xci1604_4 [71] C. M. Steele, "A threat in the air: How stereotypes shape intellectual identity and performance," American Psychologist, vol. 52, no. 6, pp. 613-629, 1997. https://doi.org/10.1037/0003-066X.52.6.613 [72] G. M. Walton and G. L. Cohen, "A question of belonging: Race, social fit, and achievement," Journal of Personality and Social Psychology, vol. 92, no. 1, pp. 82-96, 2007. https://doi.org/10.1037/0022-3514.92.1.82 [73] N. i. S. Nasir and V. M. Hand, "Exploring sociocultural perspectives on race, culture, and learning," Review of Educational Research, vol. 76, no. 4, pp. 449-475, 2006. https://doi.org/10.3102/00346543076004449 https://doi.org/10.1007/s11423-015-9370-0 https://doi.org/10.1111/j.1467-9280.2006.01693.x https://doi.org/10.1080/00461520.2014.965823 https://doi.org/10.1207/s1532690xci1604_4 https://doi.org/10.1037/0003-066X.52.6.613 https://doi.org/10.1037/0022-3514.92.1.82 https://doi.org/10.3102/00346543076004449