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Abstract

Education 4.0 emphasizes the use of hybrid approaches in the learning process. The use of peeragogy, heutagogy, and cybergogy may engage students in the learning processes in which active learning plays a key role. This study aimed to examine the effect of the implementation of the Merdeka Curriculum on active learning practices and their relationships with hybrid activities based on hybrid learning approaches, and active learning counterparts of (1) self-regulated learning: (2) self-directed learning, and (3) self-determined learning. These relationships will be examined in Indonesian curriculum implementation in which student-centered principles are emphasized. A cross-sectional survey was conducted by collecting responses of vocational high school students on survey. The digital questionnaire was sent to 600 Indonesian students, of whom 555 completed it. The relationships among the constructs were examined using a structural equation modeling. The results showed that a curriculum emphasizing student-centered principles was fully mediated by active learning and hybrid activities to promote student self-regulated learning (SRL), self-determined learning (SDET), and self-directed learning (SDL). Active learning and hybrid activities directly affect students’ SRL, SDET, and SDL, Three counterparts of active learning that form important parts of long-life learning. This model indicates that Indonesian curriculum implementation may encourage active learning and indirectly increase learner engagement, autonomy, and metacognitive development.

Keywords

active learning hybrid activities self-determined learning selfdirected learning self-regulated learning curriculum implementation

Introduction

Education 4.0 is a new concept that has various definitions. Education 4.0, based on Industry 4.0, demands on some technology-related competencies (Fidalgo-Blanco et al., 2022; González-Pérez & Ramírez-Montoya, 2022; Katyeudo & de Souza, 2022). Education 4.0 encourages educational innovation to meet new challenges.

Some innovations may include designing and developing new educational practices (Winks et al., 2020). One innovation is the use of emerging technology to improve educational output and promote the use of a combination of peeragogical, heutagogical, and cybergogical approaches in the learning process (Miranda, Navarrete et al., 2021). The combination and assimilation of these approaches provide the best results in educational settings (Hanafi, 2021). Peeragogical, heutagogical, and cybergogical approaches may engage students’ in the learning process (Bizami et al., 2023). However, the use of heutagogical activities is more suitable for vocational students because it aims not only at learning but also at capability development (Hase & Kenyon, 2001).

Any method of instructing students in the learning process can be considered as active learning (Prince, 2004). Active learners as agents in active learning are defined as those who take responsibility for and manage their learning (Mou, 2021). Under this definition, active learning techniques are associated with self-regulated learning (SRL).

Learners are considered active participants in the SRL process (Pintrich, 2004). In active learning environments, students may enhance their self-regulation of learning (Manganello et al., 2019). Self-determined learning is also related to active learning by motivating students to become active in the learning process (Jeno, 2015). Both SRL and self-determined learning require active learning (Loyens et al., 2008). Self-directed learning is another concept closely aligned with active learning. Self-directed learning emphasizes learners’ ability to take responsibility for their own learning experiences, make informed decisions, and manage their learning processes independently (Geng et al., 2019; Knowles, 1977; Long, 1994). Active learning methods have been discovered to be closely aligned with the fundamental principles of self-directed learning through the facilitation of learner autonomy and initiative. (Nasri, 2017; O’Shea, 2003).

Active and student-centered learning as the main aims of the Indonesian Merdeka Curriculum may also be related with self-regulated, self-determined, and self-directed learning. There has been research on the effect of active learning on self-regulated(Bell & Kozlowski, 2008; Sletten, 2017; Wolters et al., 2023), self-determined (Chiu, 2022; Khayat et al., 2021), and self-directed learning (Y. Choi et al., 2017; Khayat et al., 2021; Li et al., 2021; Topale, 2016).However, few studies have investigated the specific impact of active learning on self-regulated, self-determined, and self-directed learning. . Understanding how active learning strategies contribute to the development of learners’ self-regulation skills, autonomy, and motivation is crucial for effective educational practice in the context of Education 4.0.

In the investigation of the relationships, hybrid activities will be included as moderator variable and Indonesian curriculum implementation will be evaluated. The Indonesian curriculum has promoted the student-centered learning through Curriculum 2013 (Prihantoro, 2014) and the active student learning methods curriculum (Riyan Rizaldi & Fatimah, 2022; Wahyuni, 2016) . After the adoption of Curriculum 2013, the Indonesian curriculum was revised twice, the Prototype curriculum in 2019 (Firman et al., 2022; Rosmana et al., 2022) and the Merdeka Curriculum in 2020 (Nurdyansyah et al., 2022; Pertiwi et al., 2022). These newer curricula still encourage student-centered learning similar to their predecessor. The pandemic has promoted the use of the innovative pedagogies of heutagogy and cybergogy which have emerged as popular approaches (Stukalo & Simakhova, 2020). In the post-pandemic era, the Indonesian school curriculum is based on these approaches. Hence, understanding the effects of curriculum implementation and the hybrid approach on active learning and student-centered learning will provide new insights into curriculum development. The primary objective of this study is to investigate the relationship between active learning and its impact on self-regulated learning, self-determined learning, and self-directed learning. Additionally, the research aims to explore the mediating role of the peeragogy-cybergogy-heutagogy approach in this relationship. Furthermore, this study examines the effect of the implementation of the Merdeka Curriculum on active learning practices. In doing so, this study aims to contribute to a deeper understanding of effective instructional practices and curriculum development efforts that enhance learner engagement, autonomy, and metacognitive development in the Indonesian educational context.

In a student-centered learning environment, students are active agents at the center of the educational processes (De Waard, 2017). Learning processes that take students as their focus and makes them active agents have emerged as self-regulated, self-directed, and self-determined learning (Agonács et al., 2020). Self-directed skills may be encouraged in someone entering adulthood (Knowles, 1977), the life phase of people aged 18 to 25 years (Arnett, 2000). This definition thus considers vocational high school students, especially those in their last year of high school, emerging adult. Vocational high school students also fit the curriculum implemented in elementary and secondary schools.

Literature Review

Implementation of the Merdeka Curriculum and Active Learning

The Indonesian Ministry of Education and Culture responded to the Covid-19 pandemic by restructuring the Indonesian curriculum, since the pandemic has made offline classes distance classes. The emergency curriculum was developed in August 2020 by simplifying the curriculum content to focus on the basic skills and knowledge students need. The emergency curriculum was then improved into the Merdeka Curriculum (engaging curriculum), which focuses on the simplicity and flexibility of the curriculum (Badan Standar Kurikulum dan Asesemen Pendidikan, 2021).

The Merdeka curriculum was evaluated by investigating (1) school management and planning, and (2) learning processes. The learning process evaluation includes (1) implementation of project-based learning on Pancasila value, (2) student-centered learning, (3) assessment and learning integration, and (4) students’ level of learning (Indonesian Ministry of Education Culture Research and Technology, 2022).

The student-centered learning applied in the Merdeka Curriculum may be connected to active learning. Active learning is defined as any instructional methods used to engage students in a learning process (Prince, 2004; Shroff et al., 2021). One way to engage students is to shift from teacher-centered to student-centered learning (Freeman et al., 2014; A. M. Kim et al., 2019). Project-based learning, as part of the Merdeka Curriculum, is also an active form of student-centered learning (Isa & Azid, 2021). Project-Based Learning (PBL) places students’ individual interests and needs at the focal point of the learning process, prioritizing student autonomy (J. Choi et al., 2019; Morgan, 1983; Thomas, 2000). We accordingly propose the following hypothesis:

H1: Merdeka Curriculum implementation significantly encourages active learning in the classroom.

H2: Merdeka Curriculum implementation positively affects hybrid activities in the classroom.

H3: Merdeka Curriculum implementation positively affects student self-determined learning.

H4: Merdeka Curriculum implementation positively affects student self-directed learning.

H5: Merdeka curriculum implementation positively affects student self-regulated learning.

Active Learning and Hybrid Activities

Throughout history, active learning has been recognized as a potent teaching technique and an efficient instructional approach that boosts student learning and motivation (DeWinstanley & Bjork, 2002; Michael, 2006). Active learning is rooted in equipping learners with the essential skills and strategies required to become self-directed learners (van Hout-Wolters et al., 2000). In an active learning environment, learners are encouraged to participate in the learning process by utilizing various learning strategies and engaging in self-directed learning. Consequently, they can personalize their learning experience by connecting with their learning environment and peers (Fritz, 2002; Pintrich, 1999).

Hybrid activities were developed using peeragogical, heutagogical, and cybergogical approaches. These three approaches can interact to improve student engagement (Hanafi, 2021) and constitute the foundations of learning process in Education 4.0 (Miranda, Ramírez-Montoya, & Molina, 2021; Miranda, Navarrete et al., 2021).

Heutagogy takes a comprehensive approach to fostering learner competencies, viewing learning as an active and proactive process in which learners play a crucial role as primary agents. Learning occurs through personal experiences (L. M. Blaschke, 2012; Hase & Kenyon, 2007). There are four principles of heutagogy: (1) the human as an agent of learning, (2) capability, (3) self-reflection and double-loop learning, and (4) non-linear learning (L. M. Blaschke, 2012).

The first is the human as an agent of learning. This principle pertains to the students’ desire to learn something of their own volition through their preferred learning approach (Bandura, 2001; L. M. Blaschke, 2021). As the driving force behind their learning journey, students have the autonomy to make choices regarding the methods and topics they wish to learn (Bizami et al., 2023). Second is capability. This principle emphasizes the students’ ability to apply the knowledge and skills they have acquired in a new or unfamiliar contexts (L. M. Blaschke & Hase, 2016). This can be accomplished by incorporating a curriculum that encourages students to interact with real-world situations (Stoten, 2020).

The third principle involved self-reflection and double-loop learning. These two capabilities are interrelated (Bizami et al., 2023). Students must reflect on their learning processes to develop metacognitive and self-regulatory skills, students need to be reflective in their learning process (Gregory et al., 2018) . This can be achieved through active thinking during the learning process (Canning & Callan, 2010). The fourth is non-linear learning. The traditional method of teaching and learning involves instructors having complete control over how knowledge is imparted. However, in the context of modern education, students are empowered to take charge of their learning by exploring diverse learning avenues and adapting adaptable and dynamic approaches (Gregory et al., 2018; Hase, 2016).Peeragogy highlights the roles of peers and groups in maintaining knowledge. Paragogues are individuals who learn from their peers using shared spaces for learning, networks spread over various locations, and virtual communities to acquire knowledge (Mulholland, 2019). Peeragogy has five basic principles: (1) decentered center context, (2) meta-learning serves as a source of knowledge, (3) feedback that is not typically available is provided by peers, (4) learning is distributed and not linear, and (5) if possible, one should seek to achieve one’s aspirations, but be prepared to wake up and face reality (Corneli & Danoff, 2011b).

The first is the decentered center context. In the peeragogically context, we acknowledge that we are not just educators or students, instead, we collaboratively construct an entire learning environment. Second, meta-learning serves as a source of knowledge. Peeragogy focus is on both attempting to “learn how to learn” and on acquiring the skills to aid others in their learning endeavors (Smith, 1983). Third, peers provide feedback that is not typically available. Learners should not only seek affirmation of their existing knowledge, but also engage with and comprehend different perspectives as a fundamental aspect of the learning process (Corneli & Danoff, 2011).

Fourth, the learning is distributed and non-linear. In peeragogy, the learning process is non-linear which means students participate in the collaborative construction of the learning environment (Corneli & Danoff, 2011; Fischer & Granott, 1995). The fifth principle is to realize one’s dream and wake up. Paragogues clearly defined their learning goals as the achievement of their objectives. They also critically evaluate their learning objectives which may have lead to modifications. This critical evaluation process makes the learning process predominantly active (Ericsson et al., 1993).

Cybergogy is an educational approach that concentrates on involving students in an online setting to enhance their cognitive, emotional, and social learning (Wang & Kang, 2006). Cybergogy comprises three principles. The first is the cognitive factor. The term “cognitive factor” refers to the various components that can impact a student’s ability to comprehend knowledge in a cybergogy-based classroom. These components include the students’ previous knowledge, learning objectives, type of learning activity, and cognitive/learning style (Muresan, 2014; Tran & Van Nguyen, 2020; Wang & Kang, 2006).

Second is the emotive factor. This principle highlights the importance of students’ psychological well-being and the dynamics among members of their learning communities. Consequently, students’ self-efficacy, self-confidence, and self-competence are integrated throughout the learning process (Wang & Kang, 2006).

Third is the social factor. This pertains to the social background of students’ identity and their sense of community, which can be developed through collaborative activities (Wang & Kang, 2006). These activities usually occur online and are led by instructors to facilitate student engagement (Qismullah & Yusuf, 2018).

Peeragogical and heutagogical principles and technological capabilities (cybergogy) are crucial for creating engaging immersive learning environments that facilitate effective learning (L. Blaschke, 2018). This aligns with Kaufman’s (2019) recommendation that a redesign of transformative instructional blended learning should encompass both pedagogical components and technological tools to foster active learning experiences and student-centered approaches. Accordingly, we hypothesize:

H6: Active learning may affect the use of hybrid activities.

Active Learning, SRL, SDET, and SDL

Active and self-regulated learning share several common elements. In both learning scenarios, the learner is actively engaged, thinking critically, and reflecting on their learning experiences, while the teacher plays a role in supporting and motivating the learners (Virtanen et al., 2017). Active learning encompasses not only physical activity but also mental engagement (Mirriahi et al., 2021). To mentally engaged with the content, students need to regulate their learning (Panadero, Jonsson, & Botella, 2017).

In the constructivist framework, active learning should include self-directed learning and active mental engagement (Y. Choi et al., 2017). In active learning, self-determined learning includes a process that increase student participation (Knight & Wood, 2005). To encourage students to explore their own interests and become active participants in their learning, certain active learning approaches encourage them to develop their own hypotheses, create experimental designs, and tackle open-ended problems (DebBurman, 2002; Gehring & Eastman, 2008).

Active learning is associated with self-directed learning. Self-directed learners are motivated by their intrinsic desire to learn and readily embrace learning challenges, which enables them to be actively involved and actively participate in the learning process (Navaitienė & Stasiūnaitienė, 2021). Active learning and self-directed learning align with each other with respect to learners’ engagement in various activities, whether they are small-scale activities like discussions, writing, presentations, or problem-solving, or larger activities that involve reflection (Navaitienė & Stasiūnaitienė, 2021). The combination of active and self-directed learning has created new concept of deep active learning (Matsushita, 2018). Accordingly, we hypothesize:

H7: Active learning positively affects student self-determined learning.

H8: Active learning positively affects student self-directed learning.

H9: Active learning positively affects student self-regulated learning.

Hybrid Activities, SRL, SDET, and SDL

Hybrid activities are derived from the hybrid of cybergogy, peeragogy, and heutagogy. In the context of cybergogy, the traditional role of teachers as the sole providers of information is no longer prevalent. Instead, cybergogy empowers learners to have direct control over their acquisition of knowledge. This aspect of cybergogy is particularly advantageous for self-directed learners (Norsamsinar et al., 2022). The cognitive factor of cybergogy is also related to students’ self-regulated learning, a type of cognitive engagement (Wang & Kang, 2006).

Heutagogy, as a part of the hybrid approach, promotes learning as a self-determined process in which learners have the freedom and agency to direct their own learning journeys (Chan et al., 2019; Hase, 2014). It encourages individuals to take ownership of their learning, set their own goals, and actively engage in the learning process based on their interests and needs. The peeragogical principle of meta-learning is associated with student metacognition (Bizami et al., 2023). Students in peeragogical classroom are aware of their own learning processes. This awareness involves actively monitoring and reflecting on how they learn, identifying their strengths and areas for improvement, and making intentional choices to enhance their learning experience (Corneli & Danoff, 2011). Accordingly, we hypothesize:

H10: Hybrid activities positively affects student self-determined learning.

H11: Hybrid activities positively affects self-directed learning.

H12: Hybrid activities positively affects student self-regulated learning. The stated hypothesis in this study is displayed in Figure 1.

Figure 1.

Framework of the relationship between variables.

Methods

The present empirical study is a quantitative no experimental study. A cross-sectional survey was sent to the vocational school students in two provinces in Indonesia, South and West Sulawesi. The survey was given to the students through their teacher’s concern and help. The survey was conducted after obtaining institutional ethics approval from our university. The survey consisted of 85 items related to the variables used in the study.

The data gathered from the students was analyzed using a structural equation model with partial least square parameter estimation (PLS-SEM). PLS-SEM is powerful than CB-SEM, can be applied on non-normal data and a relatively small sample size (Hair et al., 2012). PLS-SEM is also recommended over CB-SEM when the model is complex and aims to test the theoretical framework (Hair et al., 2019). Both types of SEM also have potential bias. However, PLS-SEM tend to have more power to minimize the biases (Reinartz et al., 2009; Sarstedt et al., 2016).

Procedures and Participants

The participants in this study were vocational high school students in South and West Sulawesi, two provinces of Indonesia. Students participated voluntarily and provided informed consent in the first part of the survey. The digital questionnaire was sent to 600 Indonesian students, of whom 555 completed it. This can be considered as sufficient sample for PLS-SEM which requires sample of 5 to 10 times the number of items in the survey (Hair et al., 2021). Informed consent also gave researchers permission to use the data from for analysis. Of the respondents included in the study, 67% were male, and 33% female.

Instruments

Active learning used in this study focuses on the instruction paradigm. This means that the instrument contains teachers’ classroom instruction to encourage students’ active learning. Curriculum implementation was measured using documents provided by Indonesian Ministry of Education and Culture. This document provided the indicators that instructors are required to achieve to ensure the best implementation of the curriculum. However, we focused on learning-related indicators that could be observed by students. Active learning was measured using brief version Shroff et al. (2021) learner’s perception on active learning

Hybrid activity instruments were developed using the principles of peeragogy, heutagogy, and cybergogy. Self-directed, self-regulated, and self-determined learning were also measured using brief versions of existing instruments. The items were selected based on their fit within the Indonesian context. All item responses were in the form of 10-point semantic differential responses ranging from 1 (=totally disagree) to 10 (=totally agree). Table 1 displays all items used in the research questionnaire.

Table 1.

The factors of the constructs.

Variable	Factors
Curriculum implementation (Indonesian Ministry of Education Culture Research and Technology, 2022)	1. Implementation of project-based learning on Pancasila Value
	2. Student-centered learning
	3. Assessment and learning integration.
	4. Students’ level of learning
Learner’s perception on active learning (Shroff et al., 2021)	1. Engagement
	2. Cognitive processing
	3. Orientation to learning.
	4. Readiness to learn.
	5. Motivational orientation
Hybrid activities (Bizami et al., 2023; Lisa Marie, 2019)	1. Peeragogical activities
	2. Cybergogycal activities
	3. Heutagogical activities
Self-directed learning (Ayyildiz & Tarhan, 2015)	1. Attitude toward learning
	2. Responsibility toward learning
	3. Self-confidence and motivation
	4. Ability to plan learning
	5. Ability to take advantage of learning opportunities
	6. Ability to manage information
	7. Ability to use learning strategies
	8. Assessment of the learning process
	9. Evaluation of the results obtained
Self-regulated learning (Barnard et al., 2009; Korkmaz & Kaya, 2012)	1. Goal setting
	2. Structuring the environment
	3. Strategies for doing assignments.
	4. Time management
	5. Seeking help
	6. Self-sufficiency
Self-determined learning (Mumbardó-Adam et al., 2018)	1. Capacity
	2. Perception
	3. Learning at school
	4. Study at home

Result

The PLS-SEM analysis consist of two steps: a measurement model and a structural model (Hanafiah, 2020; Lee et al., 2011). The measurement model was used conducted to check the reliability and validity of items and latent variables (Lin et al., 2020) whereas the structural model investigated the relationships between latent variables (Hair et al., 2021).

Measurement Model

Assessing the measurement model using PLS-SEM involves four steps: (1) examining item loadings, (2) assessing internal consistency, (3) examining convergent validity, and (4) checking discriminant validity (Hair et al., 2019).

The factor loadings of the items should be a minimum of 0.708 which indicates that the latent variable explains a minimum of 50% of the items variance (Hair et al., 2021). However, loadings ranging between 0.4 and 0.7 should be excluded only if excluding the item increases the reliability of its construct to the suggested threshold (Hair et al., 2011). Items marked “out” in Table 2 have loadings that did not exceed the 0.4 threshold, so they are excluded from the model.

Table 2.

Factor Loadings, Composite Reliability, and AVE of Items and Constructs.

Variables	Dimension	Items	Loadings	Composite reliability	AVE
Perception on active learning		ACT1	0.747	0.965	0.648
		ACT2	0.748
		ACT3	0.824
		ACT4	0.807
		ACT5	0.845
		ACT6	0.77
		ACT7	0.826
		ACT8	0.846
		ACT9	0.857
		ACT10	0.837
		ACT11	0.793
		ACT12	0.741
		ACT13	0.829
		ACT14	0.829
		ACT15	0.766
Peeragogy-Cybergogy-Heutagogy (PCH)	Peeragogy	PEER1	0.805	0.967	0.53
		PEER1	0.805
		PEER2	0.816
		PEER3	0.782
		PEER4	0.72
		PEER5	0.812
		PEER6	0.742
		PEER7	0.732
		PEER8	0.707
		PEER9	0.764
		PEER10	0.717
		PEER11	0.575
		PEER12	0.682
	Cybergogy	CYB1	0.743
		CYB2	0.64
		CYB3	0.683
		CYB4	0.673
		CYB5	0.724
		CYB6	0.6
		CYB7	0.574
	Heutagogy	HEU1	0.687
		HEU2	0.821
		HEU3	0.807
		HEU4	0.777
		HEU5	0.757
		HEU6	0.781
		HEU7	0.728
Curriculum implementation		IMP1	0.508	0.872	0.54
		IMP2	0.685
		IMP3	0.685
		IMP4	0.633
		IMP5	0.404
		IMP6	0.314
Self-directed learning		SDL1	0.664	0.928	0.501
		SDL2	0.676
		SDL3	Out
		SDL4	0.728
		SDL5	0.619
		SDL6	Out
		SDL7	Out
		SDL8	0.781
		SDL9	0.645
		SDL10	0.676
		SDL11	Out
		SDL12	0.638
		SDL13	0.773
		SDL14	0.661
		SDL15	0.757
		SDL16	0.727
		SDL17	Out
		SDL18	0.776
Self-regulated learning		SRL1	0.736	0.933	0.541
		SRL2	0.837
		SRL3	0.67
		SRL4	0.649
		SRL5	0.759
		SRL6	0.768
		SRL7	0.777
		SRL8	0.776
		SRL9	0.517
		SRL10	0.695
		SRL11	0.777
		SRL12	0.805
Self-determined learning		SDE1	0.565	0.915	0.575
		SDE2	0.742
		SDE3	0.802
		SDE4	0.726
		SDE5	0.793
		SDE6	0.785
		SDE7	0.813
		SDE8	0.808

The internal consistency of the constructs was measured using composite reliability. PLS-SEM has three types of construct reliability: (1) Cronbach’s alpha, (2) rho A, and (3) composite reliability. Among these reliability measurements, composite reliability has been recommended over other measures. Composite reliability considers the differential weights of items (Henseler et al., 2015), whereas Cronbach’s alpha treats the indicator’s equally (Hair et al., 2017). The composite reliability of the constructs should exceed a threshold of 0.7 to be deemed a reliable construct (Hair et al., 2021). All constructs had a composite reliability score higher than 0.7. In other words, the model constructs were reliable.

Average variance extracted (AVE) is a metrics that summarizes the variance extracted from all item loadings onto their respective constructs (Hair et al., 2017). The rule of thumbs criterion for the AVE is 0.5 (Sarstedt et al., 2022). The results of the measurement model showed that all constructs had an AVE > 0.5.

The last metrics evaluated in the measurement model was discriminant validity. This type of validity investigates how different the constructs of the model are. Discriminant validity can be evaluated using the following metrics: (1) the Fornell-Larcker criterion, (2) cross-loadings, and (3) the Heterotrait monotrait ratio (HTMT) (Lin et al., 2020). Of these, however, HTMT is the preferred metrics for discriminant validity (Henseler et al., 2015). HTMT contrasts the correlation between items measuring different constructs with those measuring the same construct, whereby two constructs with an HTMT ratio closer to 1 will be regarded as more similar constructs (Sarstedt et al., 2023). Table 3 indicates that all constructs had an HTMT below 0.9, indicating that they have appropriate discriminant validity (Sarstedt et al., 2023; Voorhees et al., 2016).

Table 3.

Heterotrait Monotrait Ratio of Constructs.

Variables	Active learning	Curr. implementation	PCH	Self-determined learning	Self-directed learning
Curr. implementation	0.829
PCH	0.898	0.891
Self-determined learning	0.875	0.723	0.833
Self-directed learning	0.863	0.745	0.831	0.897
Self-regulated learning	0.869	0.734	0.83	0.841	0.892

Structural Model

The measurement model indicated that all constructs and their respective items were valid and reliable. Thus, the constructs can be used to investigate the relationships among variables in the framework. To obtain relationships through hypothesis testing, a structural model can be constructed using the bootstrap method with 10,000 replications (Sarstedt et al., 2023; Streukens & Leroi-Werelds, 2016).

The bootstrap results in Table 4 showed that curriculum implementation significantly affected active learning $(β = 0.76, t = 25.564, p < . 001)$ . Curriculum implementation also showed a significant effect on the hybrid activities of the students $(β = 0.837, t = 46.923, p < . 001)$ . Similar results were also shown for the relationships between curriculum implementation and self-determined learning $β = 0.642, t = 16.907, p < . 001$ , curriculum implementation and self-directed learning $(β = 0.661, t = 20.621, p < . 001)$ , and curriculum implementation and self-regulated learning $(β = 0.657, t = 21.24, p < . 001)$ . Curriculum implementation is fully mediated by active learning and hybrid activities in its effects on self-determined, self-directed, and self-regulated learning.

Table 4.

Bootstrap Results on Total Effect of the Constructs.

Constructs	Coef.	t	p
Curr. implementation → Active learning	0.76	25.564	.000
Curr. implementation → PCH	0.837	46.923	.000
Curr. implementation → Self-determined learning	0.642	16.907	.000
Curr. implementation → Self-directed learning	0.661	20.621	.000
Curr. implementation → Self-regulated learning	0.657	21.24	.000
Active learning → PCH	0.544	11.048	.000
Active learning → Self-determined learning	0.791	18.293	.000
Active learning → Self-directed learning	0.746	18.491	.000
Active learning → Self-regulated learning	0.761	17.911	.000
PCH → Self-determined learning	0.355	4.932	.000
PCH → Self-directed learning	0.339	5.256	.000
PCH → Self-regulated learning	0.333	4.58	.000

Fully mediated variable is one that shows no direct effect on a specific variable has a significant indirect effect it (J. Kim et al., 2018). Curriculum implementation has an insignificant effect on self-determined learning $(β = - 0.109, t = 1.856, p < . 001)$ , self-directed learning $(β = - 0.05, t = 0.948, p < . 001)$ , and self-regulated learning $(β = - 0.063, t = 0.948, p < . 001)$ (Table 5).

Table 5.

Bootstrap Results for the Direct Effect of Constructs.

	Coef.	t	p
Curr. implementation → Active learning	0.76	26.726	.000
Curr. implementation → PCH	0.423	8.336	.000
Curr. implementation → Self-determined learning	−0.109	1.856	.063
Curr. implementation → Self-directed learning	−0.05	0.948	.343
Curr. implementation → Self-regulated learning	−0.063	1.273	.203
Active learning → PCH	0.544	11.041	.000
Active learning → Self-determined learning	0.598	9.032	.000
Active learning → Self-directed learning	0.562	9.865	.000
Active learning → Self-regulated learning	0.579	9.586	.000
PCH → Self-determined learning	0.355	4.91	.000
PCH → Self-directed learning	0.339	5.137	.000
PCH → Self-regulated learning	0.333	4.653	.000

Student perceptions of active learning had a significant effect on hybrid activities $(β = 0.423, t = 8.336, p < . 001)$ , as well as significant total effects on self-determined learning $(β = 0.791, t = 1.856, p < . 001)$ , self-directed learning $(β = 0.746, t = 0.948, p < . 001)$ , and self-regulated learning $(β = 0.761, t = 0.948, p < . 001)$ . Since active learning also showed significant direct effects on self-determined learning $(β = 0.598, t = 9.032, p < . 001) [0, 1]$ , self-directed learning $(β = 0.562, t = 9.865, p < . 001)$ , and self-regulated learning $(β = 0.579, t = 9.586, p < . 001)$ , we may conclude that active learning has a partially mediating effect on these variables (J. Kim et al., 2018).

Students’ hybrid activities showed significant effect on self-determined learning $(β = 0.355, t = 4.91, p < . 001)$ and a significant effect on self-directed learning $(β = 0.339, t = 5.137, p < . 001)$ and self-regulated learning $(β = 0.333, t = 4.653, p < . 001)$ .

Discussion

This present study sought to investigate the relationship between active learning and its effects on self-regulated, self-determined, and self-directed learning within the context of the Indonesian Curriculum (Merdeka Curriculum). Our findings contribute to research by providing a comprehensive examination of these interconnected constructs within the context of education.

This study investigated the impact of the implementation of the Merdeka Curriculum on active learning and its counterparts. The findings indicate that the Merdeka Curriculum, which emphasizes student-centered learning and individualized instruction, aligns well with the principles of active learning. The curriculum’s focus on students’ needs, capabilities, and interests provides an environment conducive to the implementation of active learning strategies (Pertiwi et al., 2022; Riyan Rizaldi & Fatimah, 2022). Curriculum implementation had a positive relationship with hybrid activities. The Covid-19 pandemic prompted technology-mediated learning process which is also included in Merdeka Curriculum (Maipita et al., 2021). The technology-mediated learning process is also called cybergogy (Bizami et al., 2023) which is an innovative pedagogy, along with heutagogy and peeragogy.

The results also show that curriculum implementation has an insignificant direct effect on self-regulated, self-determined, and self-directed learning. This results is supported by the fact that the Merdeka Curriculum does not explicitly encourages this active learning counterparts (Indonesian Ministry of Education Culture Research and Technology, 2022). However, curriculum implementation focusing on online student-centered learning (Ahid & Sufirmansyah, 2022; Paramitha et al., 2021) may positively affect students’ self-regulated, self-determined, and self-directed learning by encouraging active learning and hybrid activities, as student centered learning is a form of active learning in the classroom (Michael, 2006).

The results also indicates that active learning is significantly related to hybrid activities consisting of peeragogical, cybergogical, and heutagogical activities. To promote active learning, instruction should involve pedagogical and technological approaches (Kaufman, 2019). This pedagogical approach can be reflected in heutagogical activities that are student-centric and in which students independently determine their learning (L. M. Blaschke & Hase, 2019; Kapasi & Grekova, 2018). The student-centric nature of hybrid activities may explain why curriculum implementation positively affects these activities.

Active learning has also been shown to have positively affect self-regulated, self-determined, and self-directed learning. Active and self-regulated learning are guided by shared principle. Both requires active student engagement (Virtanen et al., 2017), particularly mental engagement (Panadero, 2017). Students who actively engage in the learning process, both physically and mentally, may also regulate their learning. In more active learning, learners are empowered to take control of their own time management, select their own learning objectives and preferred activities, assess their own progress, strive independently to comprehend and master materials, and engage in self-reflection regarding both their failures and achievements (van Hout-Wolters et al., 2000). Student engagement in the classroom may foster different types of motivation in students that relate active learning with self-determined learning (Chiu, 2022). The motivations are origin motivation, autonomous motivation, and academic efficacy and the results also indicate that hybrid activities have a positive relationship with students’ self-regulated, self-determined, and self-directed learning. Hybrid activities are based on innovative pedagogies of heutagogy, cybergogy, and peeragogy. Hybrid activities may affect self-directed learning because the learning process using a heutagogical approach tends to be more active and self-directed (L. M. Blaschke, 2019). Student engagement, produced through active learning and hybrid activities, is a complex concept that can differ depending on the specific learning environment. One such dimension is self-regulated learning (Bangert-Drowns & Pyke, 2002).

Heutagogical activities may also berelated to the central concept of self-determined learning (Hase, 2016). Heutagogical activities push students toward teamworking, continuous improvement, solving problems, and thinking critically. Additionally, the principle of heutagogical activities central to self-determined learning is learning how to learn (Hase, 2016). Heutagogy also includes self-regulated learning, but it differs from the traditional method of learning led by instructors (Agonács & Matos, 2019). Another part of hybrid activities, peeragogical activities, may have affected students’ self-determined learning. Paragogues students should also learn how to learn (Smith, 1983). The critical evaluation of students’ learning objectives is also related to self-determined learning in which students critically evaluate their own learning (Hmelo & Lin, 2000; Schmidt, 1983).

Conclusion

The Merdeka Curriculum is an innovative response to a pandemic that has disrupted education systems worldwide. Teachers must adopt new and creative teaching methods to ensure that students continue to learn and grow in the face of unprecedented challenges. The Merdeka Curriculum has enabled teachers to facilitate active learning in classrooms by utilizing a range of student-centered approaches, including hybrid activities that combine online and offline learning.

A key feature of the Merdeka Curriculum is its emphasis on student-centered learning, which encourages students to take responsibility for their learning path. This approach promotes the development of essential skills and qualities such as peeragogical, heutagogical, and cybergogical activities, which involve collaboration, self-direction, and the use of technology, respectively. By fostering these skills, the curriculum helps students become more self-regulated, self-directed, and self-determined, which are essential traits for lifelong learning.

The findings of this study hold several implications for educational practice and future research. Firstly, the positive relationship between active and self-regulated learning suggests that incorporating active learning strategies into instructional design can foster students’ metacognitive skills and self-regulation abilities. Educators and curriculum developers can utilize these findings to enhance their pedagogical practices and create learning environments that promote self-regulated learning. Secondly, the study’s results highlight the importance of considering the role of self-determined learning in the context of active learning. By emphasizing learner autonomy, choice, and motivation, educators can design activities and provide opportunities to empower students to take ownership of their learning processes. This can contribute to increased engagement and satisfaction and ultimately, improved learning outcomes.

Furthermore, examination of the peeragogy-cybergogy-heutagogy approach as a mediating variable in the relationship between active learning and the examined constructs offers insights into the potential mechanisms through which these approaches interact. Future research should investigate the specific ways in which these pedagogical frameworks influence the effectiveness of active learning strategies and student learning experiences. Finally, this investigation of the impact of the Merdeka Curriculum implementation on active learning practices provides valuable information for educational policymakers and practitioners. Understanding how this curriculum promotes student-centered learning, active engagement, and self-directedness can inform ongoing curriculum development efforts and shape instructional practices that align with the demands of Education 4.0.

In conclusion, the implications of this research suggest that integrating active learning strategies, fostering self-regulated and self-determined learning, and considering the role of pedagogical approaches such as peeragogy, cybergogy, and heutagogy can help enhance educational practices and the design of learner-centered curricula. These findings provide a foundation for the further exploration and refinement of instructional approaches that promote active engagement, autonomy, and self-directedness in educational contexts.

Future Research and Limitations

While this research article provides valuable insights into the implementation of project-based learning in the Indonesian curriculum and its impact on students’ perception of active learning, it has some limitations.

Firstly, it relied on self-reported data from students, which may be subject to bias or inaccuracies. Future research could use additional methods, such as observation or interviews with teachers, to supplement these findings. Second, this was a cross-sectional study, which may bias the relationships between variables. Future research should explore this issue using longitudinal study. Finally, the respondents were chosen purposively which may constitute a source of bias. Random probability sampling is the best sampling technique for this study and should be applied in future research. Future research could also develop specific activities using innovative pedagogies.

Footnotes

Acknowledgements

The researchers wish to express their gratitude to the Directorate General of Research, Technology and Community Development (DRTPM) of the Ministry of Education and Culture of the Republic of Indonesia as a donor of Excellence Higher Education Institution Research (PTUPT).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receiving financial support for the research, authorship, and/or publication of this article: The entire process of the current research and its publication is supported by DIPA Universitas Negeri Makassar, with grant number SP DIPA - 023.17.2.677523/2023. This support is in accordance with the official decree from the Rector of Universitas Negeri Makassar, under reference number 504/UN36/HK/2023 dated June 5, 2023.

Ethic Statement

This study was conducted in accordance with the ethical standards of Research Ethic Committee of Technological Education Faculty of Universitas Negeri Makassar No. 518/UN36.2/KP/2023. All participants provided written informed consent before participating in the study. The study protocol was reviewed and approved by Research Ethic Committee of Technological Education Faculty of Universitas Negeri Makassar and all procedures were conducted in compliance with relevant regulations and guidelines. Participant confidentiality was maintained throughout the study, and all data were analyzed and reported in aggregate form to protect participant anonymity.

ORCID iDs

Amiruddin

Fiskia Rera Baharuddin

Takbir

Wirawan Setialaksana

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May student-centered principles affect active learning and its counterpart? An empirical study of Indonesian curriculum implementation

Abstract

Keywords

Introduction

Literature Review

Implementation of the Merdeka Curriculum and Active Learning

Active Learning and Hybrid Activities

Active Learning, SRL, SDET, and SDL

Hybrid Activities, SRL, SDET, and SDL

Methods

Procedures and Participants

Instruments

Result

Measurement Model

Structural Model

Discussion

Conclusion

Future Research and Limitations

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

Ethic Statement

ORCID iDs

References