Enhancing Problem Solving Skills and Concept Mastery Through the INSPIRE Learning Model: A Quasi-Experimental Study on Environmental Change Learning

Abstract

Recent evidence indicates that many high school students continue to exhibit weak problem-solving skills and incomplete conceptual understanding of environmental change, although both are critical for addressing increasingly complex ecological challenges in the 21st century. This study aims to evaluate the effectiveness of the INSPIRE learning model in enhancing problem-solving skills and conceptual mastery of environmental change among high school students. The INSPIRE model integrates e-modules, guided inquiry-based learning (GIBL), and deep learning principles into a cohesive instructional framework. A quasi-experimental design with a non-equivalent control group pretest-posttest approach was employed, involving 108 Grade 10 students in three groups: an experimental group applying the INSPIRE model, control group 1 utilising discovery learning, and control group 2 implementing guided inquiry without e-modules. Data were collected through pretests and posttests assessing problem-solving skills and conceptual mastery of environmental change, complemented by observations of the learning implementation. The results showed that students in the INSPIRE group obtained higher mean posttest scores in both problem-solving skills and concept mastery than students in the two control groups, with statistically significant differences (p < 0.05). The findings suggest that the integration of e-modules, GIBL, and deep learning principles within the INSPIRE learning model supports a more meaningful learning experience and fosters 21st-century competencies, particularly problem solving in an environmental context. Practically, the INSPIRE learning model represents a promising option for biology instruction, especially for topics that require analytical thinking, investigation, and deep conceptual understanding.

1. Introduction

Biology learning in the 21st century can no longer focus solely on the acquisition of facts and concepts, but must also foster students’ ability to understand real-world problems, analyse causal relationships, and formulate solutions based on scientific reasoning. In this context, problem-solving skills have become one of the most essential competencies, as they enable students to solve contextual problems accurately through rational thinking processes (Ilmi, 2019; Wongchantra & Nuangchalerm, 2011; Wolf, 2021; Rios et al., 2020). OECD (2019a, 2019b) and UNESCO (2020) also emphasise that such skills are required to address the increasing complexity of scientific, technological, and environmental issues in the 21st century. However, a growing body of international research indicates that students still experience difficulties in scientific reasoning, critical thinking, and evidence-based problem solving (Arifin et al., 2025; García-Carmona, 2023; Ismeirita et al., 2025; Anjiana et al., 2026; Saxton et al., 2014). These findings suggest that weak problem-solving skills remain a broad and cross-contextual educational challenge.

In Indonesia, this challenge is also evident. Results from PISA 2022 indicate that Indonesian students’ performance remains below both global and ASEAN averages (Ilmi, 2019; OECD, 2023). Studies conducted in several regions of Indonesia, including NTB, Malang, West Java, and Makassar, similarly report that problem-solving skills in senior high school biology learning are still relatively low (Karmana, 2014; Triani et al., 2018; Purwati et al., 2023). This condition suggests that biology instruction still needs to be more strongly directed toward providing students with opportunities to confront authentic problems, examine information scientifically, and develop evidence-based solutions.

In addition to problem-solving skills, mastery of environmental change concepts is also a crucial aspect of biology learning. UNESCO (2020) and the IPCC (2022) emphasise that environmental literacy requires a solid understanding of ecological mechanisms and environmental dynamics. Nevertheless, studies in various countries show that students continue to experience misconceptions and partial understanding of environmental phenomena (Bofferding & Kloser, 2015; Boon, 2010; Ardoin et al., 2018). Similar findings have also been reported in Indonesia, where students’ understanding of environmental change is often incomplete and accompanied by a persistent knowledge-action gap, that is, a condition in which environmental knowledge does not consistently translate into actual behaviour (Portus et al., 2024; Sidik et al., 2024; Suhud et al., 2025; Salshabella et al., 2025; Wals, 2012). Therefore, environmental change learning should be designed not merely to transmit information, but also to develop deeper, connected, and applicable conceptual understanding.

From a theoretical perspective, problem solving in science is a higher-order thinking process involving problem identification, information analysis, strategy design, solution implementation, and evaluation of outcomes (Polya, 1973; Jonassen, 2011). In biology learning, the success of this process is strongly influenced by the extent to which students master scientific concepts and relate them to real-world phenomena through scientific reasoning (Bybee, 2014; NRC, 2012). In environmental change topics, students are required to understand complex interactions among ecosystem components, causal relationships, and the ecological impacts of human and natural activities (Odum & Barrett, 2005; Campbell et al., 2020). In line with this, the Kurikulum Merdeka implemented in Indonesia emphasises factual, conceptual, procedural, and metacognitive knowledge (BSKAP, 2022; Kemdikbud, 2020). Consequently, effective instruction on this topic should support not only conceptual understanding, but also the use of that understanding to analyse problems and reflect on solutions.

These demands call for a learning approach that enables students to learn more meaningfully. One relevant approach is deep learning, which emphasises meaningful understanding, conceptual connectedness, knowledge transfer, and deep reflection (Biggs & Tang, 2011; Fan et al., 2023). In the Indonesian educational context, this approach is aligned with the ideas of meaningful learning, mindful learning, and joyful learning (Levin, 2024; Feriyanto & Anjariyah, 2024; Kemdikdasmen, 2025). The ability to understand, apply, and reflect on knowledge also lies at the core of cognitive process development as described by Anderson and Krathwohl (2001). Despite this, many studies show that biology teaching in schools is still frequently dominated by one-way explanation, while the use of learning technologies such as e-modules remains limited, and investigative as well as metacognitive reflective activities are not yet optimally developed (Strat et al., 2023; Ardhita & Khanafi, 2024; Apor, 2025; Muhamad Dah et al., 2024). At the international level, similar conditions have also been reported, particularly in relation to the inconsistent implementation of inquiry-based learning and the limited integration of technology (Darling-Hammond et al., 2020; Medeiros, 2014; Mohammed et al., 2020; Photo, 2025). Previous studies have also shown that guided inquiry contributes to students’ conceptual understanding, reflective thinking, and higher-order reasoning relevant to problem solving, while discovery learning has likewise been associated with improved conceptual understanding in biology learning (Ritli & Adlini, 2022; Zion & Mendelovici, 2012; Öztürk et al., 2022; Harwandini et al., 2024; Aiman et al., 2020; Komariah & Jayanti, 2022).

From an instructional design perspective, a strong learning model should not merely present a sequence of learning steps, but should also be supported by a clear theoretical foundation, syntactic structure, social system, principles of reaction, support system, and instructional effects (Joyce et al., 2015; Arends, 2012). Therefore, in response to the need for biology instruction that supports conceptual understanding, inquiry activity, and meaningful reflection in an integrated manner, the INSPIRE learning model was developed by combining three core components, namely conceptual-procedural e-modules, guided inquiry-based learning, and deep learning principles. The e-modules provide a structured foundation of essential knowledge, guided inquiry facilitates students’ active engagement in scientific processes, and the deep learning orientation ensures that the entire learning process is directed toward meaningful understanding, conceptual connectedness, and reflective thinking. What distinguishes INSPIRE from conventional guided inquiry is its systematic integration of conceptual-procedural reinforcement through e-modules, structured inquiry activity, and explicit reflection as part of the learning syntax. Accordingly, the integration of these three components is considered more likely to support meaningful, investigative, and reflective learning than when each component is implemented separately.

Preliminary studies indicate that the INSPIRE model is valid and practical for classroom implementation, yet its effectiveness in improving problem-solving skills and concept mastery in biology learning has not been widely examined. In addition, research integrating inquiry, digital technology, and deep learning into a single coherent instructional model remains limited, particularly in Southeast Asia (Hashim & Vongkulluksn, 2018). Thus, a clear research gap exists regarding the limited empirical evidence on the effectiveness of an integrated learning model that simultaneously strengthens conceptual mastery, investigative activity, and deep reflection in environmental change learning.

Based on this background, the present study aims to evaluate the effectiveness of the INSPIRE model in improving high school students’ problem-solving skills and mastery of environmental change concepts. Theoretically, this study is expected to contribute to the literature on the integration of inquiry, digital technology, and deep learning in science education. Practically, it is expected to provide empirical evidence that can support biology teachers in designing instruction that promotes scientific literacy and 21st-century competencies. Specifically, this study addresses two main research questions: (1) Is the INSPIRE model effective in improving students’ problem-solving skills? and (2) Is the INSPIRE model effective in improving students’ mastery of environmental change concepts?

2. Methodology

2.1. Research Design

This study employed a quasi-experimental design using a non-equivalent control group pretest-posttest design. This design was selected because random assignment at the individual student level was not feasible; instead, intact classes were used as the units of implementation. Randomisation was therefore conducted at the class level to determine the roles of the selected classes as the experimental group, control group 1, and control group 2.

The study involved three groups. Before the intervention, all groups completed a pretest to examine their initial levels of problem-solving skills and concept mastery. After the intervention, all groups completed a posttest using instruments with the same constructs. The experimental group received instruction through the INSPIRE learning model, control group 1 received discovery learning, and control group 2 received guided inquiry without e-modules and without explicit emphasis on deep learning principles. The research design is shown in

Table 1. Non-equivalent control group pretest posttest design, three groups.

Group	Pretest	Treatment	Posttest
E	Y11	X1	Y21
C1	Y12	X2	Y22
C2	Y13	X3	Y23

Note: E: Experimental group, implementing the INSPIRE learning model. C1: Control group 1, implementing discovery learning, a model commonly used in regular classroom instruction. C2: Control group 2, implementing the guided inquiry-based learning model, without the use of e-modules and without an emphasis on the deep learning approach. X1: INSPIRE learning model. X2: Discovery learning model. X3: Guided inquiry-based learning model. Y1: Pretest. Y2: Posttest.

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2.2. Participants

The participants were Grade 10 students (Phase E) at SMAN 1 Piyungan, Yogyakarta, Indonesia, during the 2024/2025 academic year. The population consisted of 180 students distributed across five classes. The sample was selected through cluster random sampling, resulting in three classes: X-E1, X-E4, and X-E5, with 36 students in each class, for a total of 108 participants. A second randomisation process was then conducted to assign the three classes to the experimental group, control group 1, and control group 2.

All participants were 15–17 years old, were enrolled at the same grade level, and studied the same biology topic during the same academic period. The gender distribution in each class was relatively balanced, with male and female students represented in comparable proportions. All three groups were taught by the same biology teacher, which helped minimise variation due to differences in teaching style.

None of the participants had previously studied the topic of Environmental Change, so all groups began the topic from a relatively comparable content baseline. However, all students had prior experience with inquiry-based and/or discovery-based learning in previous lessons. This condition is important because it indicates that the students were already familiar with active learning approaches, although they had not previously experienced the INSPIRE model or studied the topic of Environmental Change through that model. Because the study was conducted in regular classroom settings, students remained in their original classes throughout the study. This preserved the natural instructional context and supported the ecological validity of the quasi-experimental design.

2.3. Procedures and Intervention

The intervention was conducted over four weeks during the regular biology schedule. Each group received the same amount of instructional time, namely 3 lesson hours per week (3 × 45 min). At the beginning of the study, all groups completed a pretest. After the intervention, all groups completed a posttest assessing the same two dependent variables, namely problem-solving skills and concept mastery.

All groups studied the same topic, Environmental Change, were taught by the same teacher, and followed comparable learning objectives. The main difference across groups lay in the instructional syntax, the use of e-modules, the degree of scaffolding, and the presence or absence of explicit reflection as part of the learning sequence. Investigative activities in all relevant groups were conducted in the classroom. The intervention characteristics of the three groups are summarised in

Table 2. Comparative syntax and intervention characteristics across the three groups.

Component	INSPIRE (Experimental Group)	Discovery Learning (Control Group 1)	Guided Inquiry (Control Group 2)
Syntax	Nurturing Problem: students identify problems or gaps from environmental phenomena and formulate investigable questions Setting Up Hypothesis: students formulate hypotheses based on concepts, theories, and prior knowledge Planning Investigation: students design an investigation to answer questions or test hypotheses Investigating Empirical Evidence: students collect empirical evidence based on the designed investigation Reasoning and Concluding: students analyse evidence, reason with findings, and formulate conclusions Ending with Reflection: students reflect on the learning process, the quality of their problem-solving strategies, and the relationship between evidence and concepts	Problem Statement: students identify and formulate the problem or tentative questions Data Collection: students seek information from learning resources or observations to support concept discovery Data Processing: students organise and process the information they have collected Verification: students compare findings with concepts or principles to verify understanding Generalisation: students derive concepts or general principles from the learning process	Orientation/ Engagement: teacher introduces a phenomenon/problem and provides initial guidance Formulating Problems/Questions: students formulate investigable questions with teacher guidance Planning the Inquiry: students plan inquiry steps, tools, materials, or procedures Data Collection: students collect data or evidence through classroom-based inquiry activities Organising and Analysing Data: students analyse, interpret, and organise inquiry findings Drawing Conclusions: students formulate conclusions based on evidence and teacher-guided reasoning Generalisation: students reflect on the inquiry process and connect findings with broader concepts Communication of Results: students communicate inquiry findings orally, visually, or in written form
Instructional orientation	Integration of conceptual-procedural e-modules, guided inquiry, and deep learning principles	Regular concept discovery through teacher-guided exploration	Inquiry-based investigation without e-modules and without explicit deep learning orientation
Learning duration	4 weeks; 3 × 45 min/week	4 weeks; 3 × 45 min/week	4 weeks; 3 × 45 min/week
Topic	Environmental Change	Environmental Change	Environmental Change
Teacher	Same teacher	Same teacher	Same teacher
Use of e-module	Yes	No	No
Classroom investigation	Yes	Limited according to discovery tasks	Yes
Explicit reflection stage	Yes	No explicit final reflection stage	Not positioned as a distinct final syntax
Role of teacher	Facilitator, scaffold provider, and guide across all INSPIRE stages	Facilitator who supports concept discovery but with less structured scaffolding	Inquiry guide who provides prompts and structured support during investigation
Role of students	Study concepts, identify problems, formulate hypotheses, design inquiry, gather evidence, reason, conclude, and reflect	Explore phenomena, identify patterns, process information, verify, and generalise concepts	Formulate questions, plan inquiry, collect and analyse data, conclude, reflect, and communicate findings
Distinctive feature	Full integration of concept reinforcement, inquiry process, and explicit deep reflection	Focus on concept discovery without INSPIRE structure or e-module support	Inquiry process is present, but without conceptual-procedural e-module support and without INSPIRE’s explicit reflective closure

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In the INSPIRE group, students first built their conceptual and procedural foundation through the e-module before entering structured inquiry and reflection. In the discovery learning group, students were encouraged to derive concepts through guided exploration, but without the structured INSPIRE sequence, dedicated e-module, or explicit reflective closure. In the guided inquiry group, students engaged in inquiry processes in the classroom, but without e-modules and without the explicit integration of deep learning principles within the full learning syntax. These differences were intentionally maintained to examine whether INSPIRE offered added value over the two comparison models.

2.4. Research Instruments

This study employed three types of instruments, namely: (1) a problem-solving skills test, (2) a concept mastery test, and (3) an observation sheet for learning implementation. Each instrument served a different function. The problem-solving skills test was used to measure the outcome variable of problem-solving skills, the concept mastery test was used to measure the outcome variable of concept mastery, and the observation sheet was used to monitor the implementation of the learning models and treatment fidelity throughout the intervention. Thus, the learning outcomes in this study were not derived from a single composite score across all instruments; instead, each outcome was analysed separately according to the construct being measured.

2.4.1. Problem-Solving Skills Test

Problem-solving skills were assessed using a context-based essay test consisting of six items. The items were developed from authentic cases related to Environmental Change, so that students were required not merely to recall information, but also to analyse situations, identify problems, and propose evidence-based solutions. The six items were designed to represent key stages of problem solving, namely: (a) understanding the problem, (b) formulating strategies or solution plans, (c) implementing or explaining solution steps, and (d) evaluating the feasibility and potential impact of the proposed solutions. Student responses were scored using an analytic rubric containing several performance levels for each indicator. The rubric was intended to support a more objective evaluation of students’ responses in terms of the accuracy of problem analysis, the relevance of the proposed strategy, the clarity of the reasoning, and the quality of the evaluation of the solution. The scores across all items were then summed to obtain each student’s problem-solving score.

2.4.2. Concept Mastery Test

Concept mastery was measured using a written essay test, also consisting of six items. The items covered major indicators within the topic of Environmental Change, including: (a) types of environmental change, (b) causes of environmental change, (c) impacts on ecosystems, and (d) mitigation efforts. The items were designed to assess not only factual knowledge, but also conceptual understanding and reasoning skills. Accordingly, the targeted cognitive levels included the ability to analyse, evaluate, and create. Student responses were scored using a rubric that emphasised conceptual accuracy, completeness of explanation, and the ability to connect scientific concepts with the context of environmental change. The total concept mastery score for each student was obtained by summing the scores across all items.

2.4.3. Observation Sheet for Learning Implementation

In addition to the two learning outcome tests, this study used an observation sheet to assess the implementation of the INSPIRE model and the two comparison models during classroom instruction. The observation sheet included indicators related to: (a) the implementation of the learning syntax, (b) student activities during the lesson, and (c) teacher consistency in applying the planned instructional procedures. Observations were conducted in each session to provide a practical account of how the models were implemented and to monitor treatment fidelity throughout the intervention. This observation instrument was not used to generate students’ learning outcome scores. Instead, it functioned as a supporting instrument to evaluate treatment fidelity and the consistency of classroom implementation. Its main role was to ensure that differences in learning outcomes across groups were more likely attributable to the characteristics of the learning models rather than to inconsistencies in implementation.

In this study, the problem-solving skills test and the concept mastery test served as the primary instruments for evaluating the effectiveness of the learning models, whereas the observation sheet functioned as a supporting instrument for monitoring implementation. Accordingly, the findings were analysed in two main strands: (1) changes in problem-solving skills, and (2) changes in concept mastery. These two outcome variables were analysed separately, in line with the structure of the Results section, which reports the effectiveness of the INSPIRE model on problem-solving skills and concept mastery in two distinct analyses.

2.5. Validity and Reliability

The research instruments, which consisted of the problem-solving skills test and the concept mastery test, were developed through a process of design and expert review to ensure that the test items were aligned with the constructs being measured. Content validity was established through an expert review involving three specialists in the fields of biology education, educational evaluation, and environmental science content. The experts evaluated several key aspects, namely: (1) the alignment of the items with the indicators, (2) the adequacy and depth of the content, (3) the clarity of item wording, and (4) the consistency of the instruments with the learning objectives. Feedback from the experts was then used to revise and refine the instruments before they were piloted with students.

After the content validation stage, the instruments were piloted to obtain evidence of empirical validity. Empirical validity was analysed using item-total correlations. For the problem-solving skills test, the item-total correlation coefficients ranged from 0.368 to 0.579, while for the concept mastery test, they ranged from 0.404 to 0.652. All of these values were higher than the r-table value of 0.361, indicating that all items on both instruments were valid and adequately represented the constructs being measured.

The internal reliability of the instruments was calculated using a reliability coefficient based on the pilot-test data. The results showed that the problem-solving skills test had a reliability coefficient of 1.14, whereas the concept mastery test had a reliability coefficient of 1.15. In this study, both values were interpreted as indicating high reliability, suggesting that student responses were consistent across items and that the instruments demonstrated strong internal consistency. Therefore, both main instruments were considered suitable for consistently measuring students’ problem-solving skills and concept mastery. Overall, the results of content validation, empirical validity testing, and internal reliability analysis indicate that the instruments used in this study were appropriate for collecting the main data regarding the effectiveness of the INSPIRE learning model on problem-solving skills and concept mastery.

2.6. Treatment Fidelity

To ensure that the INSPIRE model and the two comparison models were implemented consistently throughout the study, treatment fidelity was monitored during each instructional session. This monitoring was conducted to ensure that differences in learning outcomes across groups were more likely attributable to the characteristics of the learning models rather than to uncontrolled variation in implementation.

Treatment fidelity was monitored by two trained observers who attended each classroom session. The observers used observation sheets developed in accordance with the syntax of each learning model. Using these instruments, they recorded the extent to which the instructional steps were implemented, the level of student engagement during the lesson, and the teacher’s consistency in carrying out the instructional procedures as planned.

In the INSPIRE group, the observations focused on the implementation of the model’s seven main syntaxes, namely Identifying Basic Concepts, Nurturing Problem, Setting Up Hypothesis, Planning Investigation, Investigating Empirical Evidence, Reasoning and Concluding, and Ending with Reflection. In the control groups, the observations were directed at the extent to which the instructional procedures were implemented in accordance with the respective model used, namely discovery learning and guided inquiry. Accordingly, the observations did not merely document general classroom activity, but also examined whether each group actually received the treatment as specified in the research design.

The treatment fidelity data were used as supporting evidence to show that the learning models were implemented as intended and with an adequate level of consistency. Therefore, in this study, the fidelity instrument served to strengthen the study’s internal validity, particularly by supporting the assumption that comparisons of learning outcomes across groups were based on treatments that were implemented in accordance with the research design.

2.7. Data Analysis

The data in this study were analysed using both descriptive and inferential statistics. Descriptive analysis was conducted to describe the distribution of students’ scores on the two dependent variables, namely problem-solving skills and concept mastery, both before and after the intervention. The descriptive statistics included the mean, standard deviation, minimum score, and maximum score. This analysis was used to provide an initial overview of changes in learning outcomes within each group.

To examine the effectiveness of the INSPIRE model in comparison with the two comparison models, the study initially considered the use of Multivariate Analysis of Variance (MANOVA) because the study involved two dependent variables analysed simultaneously, namely problem-solving skills and concept mastery. Before the inferential analysis was conducted, the data were tested for several statistical assumptions, including normality, homogeneity of variance-covariance matrices, and the absence of multicollinearity. These assumption tests were necessary to determine whether multivariate analysis was appropriate for the data.

However, because some of the assumptions required for MANOVA were not met, the inferential analysis was continued using one-way ANOVA separately for each dependent variable. Accordingly, group differences were examined through two univariate analyses: (1) ANOVA for problem-solving skills, and (2) ANOVA for concept mastery.

This approach was selected to ensure that the analysis remained appropriate for the characteristics of the data while still allowing a valid comparison across groups. When the ANOVA results indicated statistically significant differences, the analysis was followed by a post hoc test to identify which groups differed significantly from one another. In this study, the post hoc procedure was used to compare the position of the experimental group relative to control group 1 and control group 2 for each dependent variable. Through this procedure, the analysis did not merely determine whether differences existed among groups, but also located those differences more specifically. Overall, the combination of descriptive and inferential analyses in this study was intended to provide a comprehensive account of students’ changes in learning outcomes and to test whether the INSPIRE model demonstrated greater effectiveness than discovery learning and guided inquiry on the topic of Environmental Change.

3. Results

3.1. Implementation of the INSPIRE Learning Model

Before presenting the learning outcome data, the implementation of the INSPIRE model was examined to confirm that the instructional procedures were carried out as intended during the intervention. The observation results regarding the implementation of the INSPIRE learning model are presented in

Table 3. Implementation of the INSPIRE learning model.

Syntax	Student Activities	Implementation
1. Identifying basic concepts	Reviewing the presentation of environmental change material in IT-based self-learning modules or materials, which contain conceptual and procedural knowledge.	Successfully implemented
2. Nurturing Problem	Examining current issues/phenomena related to environmental change material to identify gaps/problems contained within. Formulating research questions related to these gaps/problems.	Successfully implemented
3. Setting Up Hypothesis	Formulating hypotheses based on existing principles, theories, and expert opinions.	Successfully implemented
4. Planning Investigation	Designing investigations to answer research questions and/or validate the hypotheses that have been formulated.	Successfully implemented
5. Investigating Empirical Evidence	Collecting data/empirical evidence based on the investigation design that has been developed.	Successfully implemented
6. Reasoning and Concluding	Organising, processing data, and formulating conclusions that provide answers to the research questions or validate the hypotheses.	Successfully implemented
7. Ending with Reflection	Conducting reflection and evaluation of the process and results, from examining issues/phenomena to the conclusions that have been made.	Successfully implemented

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As shown in Table 3, all seven syntaxes of the INSPIRE learning model, namely Identifying Basic Concepts, Nurturing Problem, Setting Up Hypothesis, Planning Investigation, Investigating Empirical Evidence, Reasoning and Concluding, and Ending with Reflection, were implemented successfully throughout the instructional process. These findings indicate that the INSPIRE model was implemented in accordance with the planned design in the classroom context of this study.

3.2. Problem-Solving Skills

The descriptive statistics of students’ problem-solving skills before and after the intervention in the three groups are presented in

Table 4. Mean scores of problem-solving skills before and after the learning process in control and experimental groups.

Statistic	Discovery Learning		Guided Inquiry		INSPIRE
	(Control Group 1)		(Control Group 2)		(Experimental Group)
	Pretest	Posttest	Pretest	Posttest	Pretest	Posttest
N	36	36	36	36	36	36
Mean	33.33	62.15	33.57	74.07	33.68	92.01
Std. Dev.	5.08	5.58	5.63	4.99	6.17	3.50
Minimum	20.83	45.83	20.83	62.50	20.83	83.33
Maximum	41.67	75.00	41.67	83.33	41.67	95.83

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As shown in Table 4, the three groups had relatively similar pretest mean scores, namely 33.33 for the discovery learning group, 33.57 for the guided inquiry group, and 33.68 for the INSPIRE group. After the intervention, the posttest mean scores increased in all groups, reaching 62.15, 74.07, and 92.01, respectively. Descriptively, the INSPIRE group showed the highest posttest mean score compared with both comparison groups.

To determine whether these differences were statistically significant, a one-way ANOVA was conducted. The results are presented in

Table 5. ANOVA results for problem-solving skills in control group 1, control group 2, and experimental group.

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	16,267.07	2	8133.54	357.14	0.00
Within Groups	2391.27	105	22.77
Total	18,658.34	107

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Table 5 shows that the difference in problem-solving scores among the three groups was statistically significant (p < 0.05). This result indicates that the groups differed in their post-intervention problem-solving outcomes.

To identify which groups differed significantly from one another, a post hoc test was conducted. The results are presented in

Table 6. Post hoc test results, location comparison of problem-solving skills between control group 1, control group 2, and experimental group.

Group	N	Subset for Alpha = 0.05
		1	2	3
Discovery Learning (Control Group 1)	36	62.15
Guided Inquiry (Control Group 2)	36		74.07
INSPIRE (Experimental Group)	36			92.01
Sig.		1.00	1.00	1.00

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Based on Table 6, the INSPIRE group had the highest mean score and occupied a different subset from the two comparison groups. The guided inquiry group showed a higher mean score than the discovery learning group, but both remained below the INSPIRE group. These findings suggest that, in the context of this study, students who learned through the INSPIRE model demonstrated more favourable problem-solving outcomes than those in the discovery learning and guided inquiry groups.

3.3. Concept Mastery

The descriptive statistics of students’ concept mastery before and after the intervention in the three groups are presented in

Table 7. Mean scores of concept mastery skills before and after the learning process in control and experimental groups.

Statistic	Discovery Learning		Guided Inquiry		INSPIRE
	(Control Group 1)		(Control Group 2)		(Experimental Group)
	Pretest	Posttest	Pretest	Posttest	Pretest	Posttest
N	36	36	36	36	36	36
Mean	35.07	62.85	35.43	74.31	35.42	93.17
Std. Dev.	4.71	4.03	4.71	6.02	4.28	2.84
Minimum	25.00	54.17	4.71	54.17	4.71	87.50
Maximum	41.67	70.83	44.00	83.33	43.67	95.83

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As shown in Table 7, the pretest mean scores were also relatively similar across groups, namely 35.07 for the discovery learning group, 35.43 for the guided inquiry group, and 35.42 for the INSPIRE group. Following the intervention, the posttest mean scores increased in all groups to 62.85, 74.31, and 93.17, respectively. Descriptively, the INSPIRE group again showed the highest posttest mean score among the three groups.

To examine whether these differences were statistically significant, a one-way ANOVA was conducted. The results are shown in

Table 8. ANOVA results for concept mastery skills in control group 1, control group 2, and experimental group.

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	16,880.09	2	8440.04	418.28	0.00
Within Groups	2118.68	105	20.18
Total	18,998.77	107

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Table 8 indicates that the difference in concept mastery scores among the three groups was statistically significant (p < 0.05). This result suggests that the three instructional models were associated with different concept mastery outcomes after the intervention.

To determine the location of these differences, a post hoc test was conducted. The results are presented in

Table 9. Post hoc test results, location comparison of concept mastery skills between control group 1, control group 2, and experimental group.

Group	N	Subset for Alpha = 0.05
		1	2	3
Discovery Learning (Control Group 1)	36	62.85
Guided Inquiry (Control Group 2)	36		74.31
INSPIRE (Experimental Group)	36			93.17
Sig.		1.00	1.00	1.00

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Based on Table 9, the INSPIRE group had the highest mean score and was positioned above both comparison groups. The guided inquiry group showed a higher mean score than the discovery learning group, but both remained below the INSPIRE group. These findings indicate that, within the context of this study, the INSPIRE model was associated with more favourable concept mastery outcomes than the discovery learning and guided inquiry models.

4. Discussion

The findings of this study show that students in the INSPIRE group obtained higher mean scores in both problem-solving skills and concept mastery than students in the guided inquiry and discovery learning groups. Statistically significant differences were also found across groups for both dependent variables. These findings suggest that, within the context of this study, the INSPIRE learning model was associated with more favourable learning outcomes on the topic of Environmental Change than the two comparison models.

One plausible explanation for these findings is that the INSPIRE learning model does not merely ask students to discover concepts or conduct inquiry activities, but also provides conceptual and procedural reinforcement through e-modules, organises the inquiry process through a clear sequence of learning steps, and closes the process with explicit reflection. This combination is particularly relevant to environmental change learning, where students are expected not only to understand information, but also to analyse causal relationships, weigh alternative solutions, and connect evidence with real-world environmental issues. In this sense, the present findings support the view that learning designs integrating conceptual support, structured investigation, and reflection may better facilitate higher-order outcomes than approaches in which these elements are implemented in a more separate or limited way.

This interpretation is consistent with Anderson and Krathwohl’s revised taxonomy and Kraiger et al.’s model of cognitive learning outcomes, both of which emphasise that meaningful learning depends not only on the accumulation of factual information, but also on the relationship between conceptual knowledge, procedural knowledge, and higher-order thinking processes (Anderson & Krathwohl, 2001; Kraiger et al., 1993). In the INSPIRE group, students were not only exposed to environmental change concepts, but also used those concepts to identify problems, formulate hypotheses, plan investigations, interpret evidence, and reflect on the problem-solving process they had undertaken. Thus, learning extended beyond knowledge acquisition toward the analytical and reflective use of knowledge. This view is also in line with Mayer’s argument that meaningful problem solving is achieved when learners actively construct knowledge through higher-order thinking rather than merely receiving information directly (Mayer, 2021).

The role of e-modules in the INSPIRE learning model appears to be one important factor supporting these outcomes. In the Identifying Basic Concepts stage, the e-module provided a structured conceptual and procedural foundation before students entered more demanding inquiry activities. Such support is important because effective investigation requires not only curiosity, but also sufficient prior understanding of the concepts, procedures, and contexts relevant to the problem under study. This interpretation is consistent with previous studies showing that well-designed e-modules can enhance concept understanding, learning independence, and cognitive learning outcomes in biology education (Tarigan et al., 2021; Kustantia et al., 2023; Syahfitri & Safitri, 2024). Other studies also report that interactive and inquiry-oriented e-modules can strengthen conceptual understanding across biology topics, including interactive e-modules on microalgae, inquiry-based and interactive e-modules in biological systems, and flipbook-based e-modules for biology learning (Akbar et al., 2024; Riyanto et al., 2024; Ayuardini, 2022). In the context of the present study, the e-module did not function merely as a digital reading resource, but as a means of strengthening students’ conceptual readiness before they engaged in classroom investigation.

The guided inquiry component of INSPIRE also appears to have contributed to the more favourable learning outcomes. The stages of Setting Up Hypothesis, Planning Investigation, Investigating Empirical Evidence, and Reasoning and Concluding allowed students to participate in scientific processes in a more structured way. Through these stages, students were expected not only to know concepts declaratively, but also to use them in investigation, evidence interpretation, and decision making. This interpretation is consistent with previous studies showing that inquiry-based learning, including guided inquiry, contributes to improved learning outcomes, critical thinking, and other 21st-century competencies (Öztürk et al., 2022; Harwandini et al., 2024; Aiman et al., 2020). Likewise, Bybee (2014) and the National Research Council (NRC, 2012) emphasise that inquiry-oriented science learning supports the development of scientific reasoning and the use of evidence in problem solving. Additional support comes from Zion and Mendelovici (2012), Ritli and Adlini (2022), and Aristawidya and Susilo (2025), who argue that guided inquiry can strengthen conceptual understanding, reflective thinking, and critical, analytical, reflective, and metacognitive reasoning. Therefore, the added value of INSPIRE does not seem to lie in replacing inquiry, but rather in reinforcing inquiry with stronger conceptual preparation and a more systematic structure.

A key distinction between INSPIRE and the two comparison models lies in the Ending with Reflection stage. In the INSPIRE group, reflection was not treated as an optional or incidental activity, but as an explicit syntax requiring students to revisit their reasoning, evaluate the quality of their problem-solving strategies, examine the strength of the evidence they had used, and connect investigation outcomes with environmental change concepts. From a deep learning perspective, this stage is important because reflection helps students build conceptual connections, review their own learning process, and transfer understanding to new situations (Biggs & Tang, 2011; Mayer, 2021). This interpretation is also consistent with studies showing that systematic reflection within investigative learning can support reflective thinking and problem-solving skills (Prayogi et al., 2025; Deniş-Çeliker & Dere, 2022; Nurhayati et al., 2023). In addition, Biggs and Tang (2011), Holmes et al. (2015), and Entwistle and Ramsden (2015) suggest that deep learning is characterised by efforts to seek meaning, connect new and prior knowledge, and respond to questions of “why” and “how”, all of which are important in learning complex biological content. Thus, the reflective closure built into INSPIRE may be one of the elements that helped students consolidate and extend their learning outcomes.

From the perspective of meaningful learning, the findings are also relevant. Meaningful learning requires that new knowledge be connected with the learner’s existing knowledge structure so that learning becomes deeper and more transferable. In INSPIRE, this connection appears to be developed through a sequence that begins with conceptual reinforcement, proceeds through problem identification and evidence-based investigation, and ends with reflection. Such a sequence enables students not only to receive knowledge, but also to reorganise, test, and reconstruct it in the context of environmental change. In this respect, INSPIRE appears more closely aligned with the orientation of meaningful learning than approaches limited to concept discovery or inquiry enactment without sufficient conceptual support and structured reflection. This interpretation is also supported by Firdaus et al. (2024), who highlight the predictive relationship between reflective thinking and critical thinking, suggesting that reflective processes may contribute to stronger cognitive outcomes.

The comparison with the two control groups also helps clarify the position of INSPIRE. In the discovery learning group, students were still engaged in concept finding, but did not receive conceptual-procedural support through specially designed e-modules, nor did they experience the integrated syntax of INSPIRE or an explicit reflective closure. In the guided inquiry group, students engaged in investigation, but without the support of e-modules and without the same explicit integration of deep learning principles. This distinction is important because previous studies have shown that guided inquiry supports students’ conceptual understanding, reflective thinking, and higher-order reasoning relevant to problem solving, whereas discovery learning has also been associated with stronger conceptual understanding in biology learning (Ritli & Adlini, 2022; Zion & Mendelovici, 2012; Öztürk et al., 2022; Harwandini et al., 2024; Aiman et al., 2020; Komariah & Jayanti, 2022). Previous literature also suggests that guided inquiry can support meaningful learning and conceptual understanding, especially when combined with structured support (Liana et al., 2022; Rahmatullah et al., 2025). However, Strat et al. (2023) and Petersen (2022) also note that the success of guided inquiry often depends heavily on the quality and consistency of teacher scaffolding. In contrast, INSPIRE appears to embed scaffolding more systematically through e-modules, guided tasks, inquiry procedures, and explicit reflection. Therefore, the present findings may be understood not as a rejection of guided inquiry or discovery learning, but as an indication that a more systematic integration of conceptual reinforcement, structured inquiry, and deep reflection may offer added value over the more limited application of these elements.

The findings also have broader theoretical implications. This study provides initial support for the proposition that biology learning which integrates e-modules, guided inquiry, and deep learning principles within a coherent instructional design may be a promising learning model for supporting both concept mastery and problem-solving skills. The main contribution of this study is not merely the separate use of digital resources or inquiry activities, but the way these components are organised into a single structured learning experience. In this regard, INSPIRE suggests that conceptual reinforcement, scientific inquiry, and reflection need not be treated as isolated components, but can instead function as a mutually supportive learning ecosystem. This interpretation is also consistent with previous work on digital biology learning resources, which has reported that interactive and inquiry-oriented digital materials can support concept mastery, self-regulated learning, and higher-order thinking (Kustantia et al., 2023; Tarigan et al., 2021; Rahmatullah et al., 2025; Liana et al., 2022).

Practically, these findings suggest that biology teachers may benefit from using learning models that do not merely emphasise investigation, but also provide sufficient conceptual support and a clear space for reflection. On topics such as Environmental Change, students need help not only in understanding scientific concepts, but also in interpreting real phenomena and evaluating solutions critically. In this respect, a learning model such as INSPIRE may represent a relevant alternative, especially because the investigations in this study were conducted in the classroom and did not require complex laboratory facilities. At the same time, effective implementation still depends on teacher readiness to manage the learning syntax, facilitate classroom investigation, and guide reflection in a meaningful way.

Nevertheless, the findings should be interpreted with caution. This study was conducted in one school, involved a limited number of participants, and focused on one biology topic, namely Environmental Change. In addition, the intervention duration was relatively short, and several external variables, such as learning motivation, technological readiness, and learning environment support, were not tightly controlled. Therefore, the present findings are better understood as empirical evidence within the specific context of this study rather than as a basis for broad generalisation. Replication in other schools, with other biology topics, and over longer instructional periods is still needed to assess the consistency of the effectiveness of the INSPIRE model across more diverse contexts.

5. Study Limitations

This study has several limitations that should be considered when interpreting the results. First, the research was conducted at a single school with a limited number of participants, so generalisation of the findings should be done with caution. The school context, student characteristics, and learning conditions may affect how the INSPIRE model functions, requiring replication in diverse populations and learning environments.

Second, the study focused solely on the topic of Environmental Change and was conducted within a relatively short teaching duration, making it unable to depict the long-term effectiveness of INSPIRE or its application to other biology concepts of varying complexity. Additionally, external variables such as student motivation, technological readiness, and learning environment support were not tightly controlled. These limitations open up opportunities for future research to conduct longitudinal evaluations and test this model in broader and more diverse learning contexts.

6. Conclusions

Based on the findings of this study, the INSPIRE learning model was associated with more favourable outcomes in both problem-solving skills and mastery of environmental change concepts than the guided inquiry and discovery learning models within the context of this study. Students who learned through the INSPIRE model obtained higher posttest mean scores on both variables, and the differences among groups were statistically significant.

These findings suggest that the integration of e-modules, guided inquiry-based learning, and deep learning principles within a structured instructional framework may support a more meaningful learning experience. In this study, the strength of the INSPIRE model appears to lie in its sequence of learning syntax, which begins with the reinforcement of conceptual and procedural knowledge, proceeds through investigative activities, and culminates in reasoning and reflection. This sequence provides students with opportunities not only to understand concepts, but also to use them to analyse problems, interpret evidence, and reflect on possible solutions.

Theoretically, this study provides initial support for the literature highlighting the importance of integrating conceptual support, inquiry processes, and deep reflection in science learning. Practically, the findings indicate that the INSPIRE model may be considered as an alternative approach in biology instruction, particularly for topics that require conceptual understanding, problem analysis, and evidence-based investigation.

Nevertheless, these conclusions should be interpreted within the boundaries of the study context, as the research was conducted in a single school, involved a limited number of participants, and focused only on the topic of Environmental Change. Therefore, the findings are better understood as empirical evidence within the context of this study, while further investigation across different schools, biology topics, and longer instructional periods is still needed to examine the consistency of the effectiveness of the INSPIRE model.

7. Recommendation

Based on the findings of this study, the INSPIRE learning model may be considered for use in biology instruction, particularly for topics that require analytical thinking, classroom-based investigation, and deep conceptual understanding. The use of INSPIRE e-modules may help students build conceptual and procedural knowledge before engaging in inquiry-based activities, while the reflective stage may support students in connecting investigation outcomes with broader scientific concepts.

For classroom practice, teachers may consider adopting structured learning designs that combine conceptual reinforcement, guided investigation, and explicit reflection, especially when teaching complex biology topics such as Environmental Change. At the same time, successful implementation of the INSPIRE model is likely to depend on teacher readiness to organise inquiry activities, guide students’ reasoning, and facilitate reflection meaningfully within regular classroom settings.

For future research, further studies are recommended to examine the effectiveness of the INSPIRE model across a wider range of biology topics, school settings, and participant characteristics. Additional studies may also investigate its implementation over a longer period in order to assess the sustainability of its effects on problem-solving skills, concept mastery, and other higher-order learning outcomes. In addition, the development of an online or hybrid version of the INSPIRE model may be considered to explore its potential use in technology-enhanced learning environments.