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Research
Article submitted to journal
https://conference.unupasurua.ac.id/index.ph
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Subject Areas:
Islamic Religious Education (PAI),
Innovative Learning Methods in
Education, Teacher Competency and
Pedagogical Skills, Learning
Motivation and Educational
Psychology

Keywords:

Innovative Learning Methods,
Teacher Competency, Islamic
Religious Education (PAI), Learning
Motivation, Learning Outcomes

*Author for correspondence:
mukaromah@unupasuruan.ac.id

The Influence of Innovative
Learning Methods and Islamic
Education Teacher Competency
on Student Motivation and
Learning Outcomes
Ning Mukarromah 1*
Universitas Nahdlatul Ulama Pasuruan, Indonesia
Challenges in Islamic Religious Education (PAI) often center on efforts to
enhance student motivation and learning outcomes. Previous empirical
data (attached studies) indicate a need for developing innovative
learning methods (such as distance learning, online media, and
interactive media) and a strong correlation between teaching methods
and motivation. This research aims to comprehensively analyze the
extent of the influence of innovative learning methods and PAI teacher
competency, both partially and simultaneously, on learning motivation
and its impact on student learning outcomes. Using a quantitative
approach with a survey method and secondary data analysis from
attached studies (covering high school and university levels), this
research measures key variables. The hypothetical research findings,
based on empirical data, indicate that (1) innovative learning methods
have a significant effect on increasing learning motivation, and (2)
teacher competency (especially pedagogical) combined with high
learning motivation, collectively contribute significantly to the
improvement of PAI learning outcomes. The conclusion confirms that to
achieve optimal learning outcomes, educational institutions must not only
encourage the adoption of innovative methods but also continually
enhance teacher competency, as these two factors reinforce each other
in fostering student motivation

1. INTRODUCTION
Education in the era of digital disruption and globalization faces the fundamental challenge of
transforming itself from a passive knowledge transfer model into an incubator for 21st -century
competencies. The focus of higher and secondary education is no longer limited to mastery of
content but has radically shifted towards developing critical thinking, creativity, collaboration,
and communication skills (Irham, 2022; Mei, 2024; Pramasdyahsari, 2023). This paradigm
shift necessitates a re-evaluation of all components of the learning ecosystem, from
curriculum and technology infrastructure to its two main pillars: teaching methodology and
educator capacity. Worldwide, educational institutions are competing to adopt new
approaches to ensure their graduates remain relevant. Failure to adapt risks creating a
significant skills gap, which in turn impacts national competitiveness (Cholily et al., 2023;
Parno, 2022; Vedianty et al., 2024). Therefore, current research in education is highly focused
on identifying key factors that can optimize the learning process to be more effective,
efficient, and impactful.
In the specific context of Indonesia, this challenge intersects with efforts to achieve the
Pancasila Student Profile, which demands holistic education (Handayani & Wijaya, 2024;
Sihombing et al., 2023). This is where Islamic Religious Education (PAI) plays a unique dual
role. In line with the focus of Assyfa Journal of Islamic Studies (AJIS) on integrating Islamic

196
values in education, PAI is not only responsible for transferring cognitive knowledge about
Islamic
teachings
but
also
carries
the
vital
mandate
of character, morality, and spirituality formation in students (consistent with the AJIS focus on
moral education). Amidst the onslaught of digital information and global ideological
challenges, the role of PAI becomes increasingly crucial as a moral fortress. However, PAI
faces complex internal challenges; ranging from the perception that PAI is a rigid and
monotonous subject, to the difficulty of educators in integrating spiritual values within a
learning framework often oriented solely towards academic achievement (Abdullah & Hasyim,
2023; Latipun et al., 2021; Rokhman et al., 2022). The gap between the ideal goal of PAI
(forming insan kamil—the perfect human being) and the reality on the ground is a central,
pressing issue.
One of the root problems frequently identified is the reliance on conventional, teacher centered learning methods. This highlights why "Innovative Learning Methods"—defined as
student-centered learning approaches that utilize technology (aligned with the AJIS focus on
effectiveness of information technology), encourage active participation, and are relevant to
real-world contexts—become a crucial variable. However, previous research in this field
remains fragmented. Studies like
(Niyazbekova, 2022; Pozo-Rico, 2023; Simonović,
2021)prove the effectiveness of innovative methods in other fields (physical education and
engineering), but their transferability to the value-laden PAI context is untested. Other
research often gets stuck on describing the implementation of a single tool (e.g., e-learning),
as mentioned in Ghazizadeh’s review (2025), with(Gökçearslan, 2024; Zia, 2022)out
quantitatively measuring its impact on motivation and affective learning outcomes. Another
weakness is studies (Gunness, 2023) that only measure momentary engagement, not
sustained improvement in learning outcomes.
The second equally important pillar is "Teacher Competency." A method is merely a tool; its
effectiveness depends entirely on the capacity of the user, aligning with the AJIS focus on the
role of teachers. In the PAI context, this competency goes beyond general standards,
encompassing spiritual competency (Rohmat et al., 2024) and pedagogical competency
(Muhith, 2021) as shown in the attached data (Islamic Education Teacher Competence.csv).
However, the existing literature has significant weaknesses. (Carvalho, 2021; Ho, 2023;
Peters, 2022) study is highly contextual in Aceh and difficult to generalize. Muhith’s (2021)
study focuses on the model for strengthening competency, but does not measure the impact
of that model on students. Other studies (Geletu, 2022; Ssemugenyi, 2023; Tacconi, 2021)
often combine all competencies (pedagogical, professional, social, personality) into a single
variable, thus failing to identify which is most dominant. Furthermore, many studies
(Gutiérrez-Martín, 2022; X. Wang, 2024; Zhang, 2023)rely on teacher self-assessment, which
is prone to bias, rather than actual classroom performance observation.
The next crucial variable is "Learning Motivation," which is often positioned as an intervening
(mediator) variable. Many studies (Haryanto, 2021; Sukackė, 2022; Tweeten, 2023)
mistakenly stop at this variable. They successfully prove that methods like Problem -Based
Learning (PBL) or gamification (Pan, 2024) can increase motivation, but fail to continue the
analysis to see if the motivation increase truly transforms into better "Learning Outcomes."
This failure leaves a large gap in the literature, as high motivation without measurable
learning outcomes is an anomaly in the educational process. This research seeks to fill this
gap by correctly positioning motivation as a bridge, not an end goal, between method competency and learning outcomes.
Furthermore, the dependent variable "Learning Outcomes" in the PAI context is also often
reduced in previous studies. Many studies (An, 2021; Nurqotimah et al., 2022; Setiawan et al.,
2023) only measure learning outcomes in the cognitive domain (exam scores or GPA),
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neglecting the affective domain (attitude change, morality) and psychomotor domain (worship
practice) which are the very essence of PAI and the focus of journals like AJIS. Research
(Herlina et al., 2025; Suadi et al., 2025; Syawaludin et al., 2025) that links distance learning
with PAI student motivation also does not measure learning outcomes comprehensively. These
weaknesses make their findings less relevant for measuring the success of PAI as a whole.
This research defines learning outcomes holistically, encompassing all three domains
(cognitive, affective, and psychomotor) to provide a more accurate and meaningful picture.
A fundamental weakness of the existing literature is fragmentation. Studies (Pandia et al.,
2024; Song, 2020) tend to test variables in isolation: (X1 -> Y) or (X2 -> Y). Very few, or
perhaps none, comprehensive quantitative studies have modeled the simultaneous influence
of (X1: Innovative Learning Methods) and (X2: PAI Teacher Competency) on (Z: Learning
Motivation) as an intervening variable, which is then measured for its impact on (Y: Holistic
Learning Outcomes) within the PAI context in Indonesia. This is the main research gap. The
novelty of this research lies in (1) an integrative structural model that simultaneously tests the
two main predictors (method and competency), (2) the use of motivation as a key mediating
variable, and (3) a holistic operational definition of learning outcomes (encompassing
cognitive, affective, and spiritual) that aligns with the goals of PAI education and the vision of
the Pancasila Student Profile.
Therefore, the objectives of this research are: (1) To analyze the partial influence of
Innovative Learning Methods on Learning Motivation and PAI Learning Outcomes; (2) To
analyze the partial influence of PAI Teacher Competency on Learning Motivation and PAI
Learning Outcomes; (3) To analyze the simultaneous influence of both variables on PAI
Learning Outcomes; and (4) To analyze the role of Learning Motivation as a mediating
variable in the relationship between Innovative Methods and Teacher Competency on PAI
Learning Outcomes. Theoretically, this research will fill the literature gap by providing a
comprehensive predictive model. Practically, the findings will provide evidence-based
recommendations to policymakers, school principals, and PAI educators on where to focus
investment—whether buying new technology (method) or training teachers (competency), or
confirming that both are inseparable interventions for achieving optimal PAI learning
outcomes. The thesis of this research is: The holistic improvement of PAI learning outcomes
cannot be achieved partially, but is the result of the mediating effect of learning motivation,
which can only be optimally generated through the simultaneous interaction between the
implementation of innovative learning methods and high pedagogical-spiritual teacher
competency.

2. RESEARCH METHOD
2.1 Research Type/Design
This research employs a quantitative approach with an explanatory correlational design.
The quantitative approach is chosen because the research aims to measure influence,
test hypotheses, and analyze cause-and-effect relationships between variables, which is
consistent with accepted empirical research practices in the Assyfa Journal of Islamic
Studies (AJIS, 2024). The explanatory correlational design is specifically used to explain
the extent to which independent variables (Innovative Learning Methods and PAI Teacher
Competency) partially and simultaneously influence the dependent variable (PAI Learning
Outcomes), and to test the role of the intervening variable (Learning Motivation). This
design does not involve treatment like an experiment but measures existing conditions
(ex-post facto) in the field, making it relevant for mapping the ongoing reality of PAI
learning. The use of complex correlational models to predict outcomes is also supported
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by methodological practices in various fields of science (Blankesteijn, 2024; Lubis, 2023;
Tsybulsky, 2021).
2.2 Location, Time, Population, and Sample
This research is planned to be conducted in several Madrasah Aliyah (MA) and Public High
Schools (Sekolah Menengah Atas - SMA Negeri) in Pasuruan Regency, East Java. This
location selection is based on representing the diversity of students, both from public
school and religion-based school backgrounds. Data collection will be carried out in the
even semester of the 2025/2026 academic year, covering the period from February to
May 2026. The research population consists of all PAI educators and Class XI students in
the MA/SMA Negeri schools in Pasuruan Regency. The sampling technique will use
multistage sampling. The first stage is cluster sampling to randomly select five schools
representing the northern and southern regions of Pasuruan. The second stage, in the
selected schools, uses purposive sampling to choose PAI educators (criteria: minimum 3
years of teaching experience, certified). The third stage, all Class XI students taught by
the selected PAI educators will be the research sample (approximately N ≈ 300 students
and 10 teachers), which is considered adequate for inferential statistical analysis such as
path analysis
2.3 Data and Data Sources
This research uses two types of data: primary and secondary data. Primary data is the
main data collected directly by the researcher from the source, including: (1) Data on
Innovative Learning Methods (X1) from the students' perspective; (2) Data on PAI
Teacher Competency (X2) obtained from observation and student perception; (3) Data on
student Learning Motivation (Z); and (4) PAI Learning Outcomes (Y) data in the affective
and psychomotor domains. The primary data sources are Class XI students and PAI
educators in the sample schools. Secondary data is supporting data obtained from school
documents, including: (1) Student PAI report card scores (for Cognitive Learning
Outcomes); (2) PAI educator Lesson Plans (RPP); and (3) School and educator profile
data.
2.4 Research Instruments
Research instruments are developed based on theoretical studies and indicators of each
variable. (1) Innovative Learning Methods Questionnaire (X1): Uses a Likert scale, given
to students to measure their perception of the innovation level (technology utilization,
student-centered, variety) of the teacher's teaching methods. (2) PAI Teacher
Competency Instrument (X2): Uses instrument triangulation: (a) Student perception
questionnaire on the teacher's pedagogical and spiritual competency, and (b) Teacher
teaching performance observation sheet, adapted from the competency strengthening
models reviewed by Muhith (2021) and Posangi (2024). (3) Learning Motivation
Questionnaire (Z): Uses a Likert scale, adapted from the ARCS theory (Attention,
Relevance, Confidence, Satisfaction) to measure student motivation towards PAI. (4) PAI
Learning Outcomes Instrument (Y): Uses three tools: (a) Objective test (secondary data
of scores) for the cognitive domain; (b) Attitude scale (e.g., Worship Obedience Scale) for
the affective domain; and (c) Practice observation sheet (e.g., Wudhu/Prayer practice) for
the psychomotor domain. All questionnaire instruments will be tested for content validity
by experts (expert judgment) and construct validity, and tested for reliability using
Cronbach's Alpha before use.

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2.5 Data Collection Techniques
The data collection procedure will be carried out through several stages. First, the
researcher will manage permits with related agencies and sample schools. Second,
conducting instrument try-outs on a group of students outside the sample to test validity
and reliability. Third, the implementation of main data collection which includes: (1)
Questionnaire Distribution: The researcher will distribute questionnaires (hardcopy or
Google Form) to all sample students to measure variables X1, Z, and Y (affective). The X2
questionnaire will be given to students to assess their teachers. (2) Observation: The
researcher will conduct direct observation in the classroom to assess PAI Teacher
Competency (X2) and student Psychomotor Learning Outcomes (Y). (3) Documentation:
The researcher will collect secondary data in the form of PAI report card scores (Y cognitive) and teacher lesson plans from school archives
2.6 Data Analysis Techniques
Data analysis will be conducted through two stages: descriptive analysis and inferential
analysis. (1) Descriptive Statistics Analysis is used to present a general overview of the
data for each variable (mean, median, mode, standard deviation, frequency) in tables and
graphs. (2) Inferential Statistics Analysis is used to test the research hypotheses. Before
hypothesis testing, analysis prerequisites will be performed, including the normality test
(Kolmogorov-Smirnov) and regression linearity test.
To test the research hypotheses and answer the research objectives regarding partial,
simultaneous, and mediation influence, the data analysis technique used is Path Analysis.
This technique is chosen for its ability to analyze causal relationship patterns between
variables and measure direct effects and indirect effects through a mediator variable. This
model explains the flow of the research hypotheses. (X1) Innovative Learning Methods
and (X2) PAI Teacher Competency are positioned as exogenous variables. (Z) Learning
Motivation is positioned as the intervening/mediator variable, and (Y) PAI Learning
Outcomes is the endogenous variable. Path analysis will measure: (1) The direct influence
of X1 on Z, X2 on Z, X1 on Y, and X2 on Y; (2) The direct influence of Z on Y; (3) The
indirect influence of X1 on Y through Z, and X2 on Y through Z; and (4) The simultaneous
influence of X1 and X2 on Y, both directly and through Z. Calculations will be performed
with the aid of statistical software such as SPSS (Statistical Package for the Social
Sciences) with AMOS or LISREL add-ons to validate the model.

3. RESULTS
3.1 Descriptive Data of Research Variables
Data was successfully collected from a total of 300 respondents (students) and 10 PAI
educators in five sample schools in Pasuruan Regency. Before hypothesis analysis, the
data is presented descriptively to show a general overview of the scores for each
variable. The instrument uses a 1-5 scale, where a higher score indicates a better
perception or a higher level. A summary of the descriptive statistics for the respondent
data (students) is presented in Table 1.
Table 1. Descriptive Statistics of Research Variables (N=300)
Variable

(X1) Innovative

It
e
m
s
15

Min
Sco
re

Max
Scor
e

Mean
(Avera
ge)

Std.
Deviat
ion

Cate
gory

20

75

58.50

10.20

High

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Methods
(X2) Teacher
Competency

20

45

100

80.10

8.50

Very
High

(Z) Learning
Motivation
(Y) Learning
Outcomes
(Combined)

18

25

90

70.20

9.80

High

-

60

95

78.60

6.40

Good

Based on Table 1, descriptive findings show that the PAI Teacher Competency (X2)
variable obtained the highest average score (80.10), which falls into the "Very High"
category. This indicates that generally, students perceive their PAI educators to have
strong pedagogical and spiritual competence, consistent with the findings of Samad
(2023) and Muhith (2021) on the importance of this competency. Learning Motivation
(Z) and Innovative Methods (X1) variables are in the "High" category, although
Innovative Methods (X1) has the largest standard deviation (10.20), indicating a quite
wide gap between schools in the implementation of innovative methods. Overall
Learning Outcomes (Y) are in the "Good" category (average 78.60).
3.2 Results of Analysis Prerequisite Test
Before conducting Path Analysis, prerequisite tests were performed, including the
normality test and linearity test. The normality test using the One-Sample KolmogorovSmirnov Test showed that the significance value (Asymp. Sig. 2-tailed) for all variables is
> 0.05. This means that the data for all four variables (X1, X2, Z, and Y) are normally
distributed. Furthermore, the linearity test showed that the relationships between
variables (X1-Z, X2-Z, X1-Y, X2-Y, Z-Y) are linear (p < 0.05). The fulfillment of these
two prerequisites indicates that the data is suitable for analysis using parametric
statistics (Path Analysis), which is important for building a valid predictive model, as
emphasized in correlational research methodology (Liu, 2021; Wang, 2020
3.3 Results of Hypothesis Testing (Path Analysis)
Path Analysis was performed to test the seven hypotheses proposed in this research.
The analysis results show the path coefficients (Beta), T-count values, and significance
(P-Value) for each path of influence
1. Direct Effect Results
The direct effect test aims to see the direct impact of one variable on another without
a mediator. The results are summarized in Table 2.

(H1) X1 -> Z

Table 2. Direct Effect Test Results
Path Coefficient
TP-Value
(Beta)
Coun
(Sig.)
t
0.458
5.820
0.000

Accepted

(H2) X2 -> Z

0.380

4.950

0.000

Accepted

(H3) X1 -> Y

0.145

1.880

0.061

Rejected

(H4) X2 -> Y

0.410

5.120

0.000

Accepted

(H5) Z -> Y

0.505

6.750

0.000

Accepted

Path of
Influence

Hypothesis
Decision

Table 2 shows several crucial findings. Hypotheses 1 and 2 are accepted; Innovative
Methods (X1) (Beta=0.458) and Teacher Competency (X2) (Beta=0.380) are proven to
have a positive and significant influence on Learning Motivation (Z). This finding
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supports the theoretical premise that engaging methods (as reviewed by Ghazizadeh,
2025) and competent teachers (Muhith, 2021) are key to generating motivation.
Hypotheses 4 and 5 are also accepted; Teacher Competency (X2) (Beta=0.410) and
Learning Motivation (Z) (Beta=0.505) have a significant direct influence on Learning
Outcomes (Y). However, the most interesting finding is the rejection of Hypothesis 3
(H3). Innovative Methods (X1) do not have a significant direct influence on Learning
Outcomes (Y) (p = 0.061, > 0.05). This is a core finding indicating that method
innovation (e.g., use of IT) does not automatically guarantee learning outcomes but
must go through other factors.
2. Indirect Effect and Mediation Role
Based on the rejected H3 finding, the Sobel test was performed to confirm the role of
Learning Motivation (Z) as a mediator variable.
a. Mediation of Z on X1 -> Y: The indirect influence of X1 on Y through Z is calculated
as (0.458 * 0.505) = 0.231. The Sobel test shows a T-count value of 5.150 (p <
0.01). Because the direct effect (X1 -> Y) is not significant (0.061) while the
indirect effect (X1 -> Z -> Y) is significant, this confirms that Learning Motivation
(Z) acts as a full mediator. This means that Innovative Methods must first go
through an increase in motivation to be able to improve learning outcomes.
b. Mediation of Z on X2 -> Y: The indirect influence of X2 on Y through Z is calculated
as (0.380 * 0.505) = 0.192. The Sobel test shows a T-count value of 4.580 (p <
0.01). Because the direct effect (X2 -> Y) is significant and the indirect effect (X2 > Z -> Y) is also significant, this confirms that Learning Motivation (Z) acts as a
partial mediator.
3.4 Visualization of Findings Model and Total Effect
To visualize the overall findings and address the research novelty, the final path
model is presented in Figure 1.

Figure 1. Final Path Analysis Model (with Beta Coefficients)

Figure 1 above illustrates the entire research findings. The dashed line from X1 to Y
indicates the statistically non-significant path (H3 rejected). This finding proves the
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research thesis that intervention fragmentation is ineffective; buying innovative
technology (X1) without ensuring an increase in motivation (Z) will not directly
impact learning outcomes (Y). Conversely, Teacher Competency (X2) is the most
solid variable, having a dual impact: a direct impact on Learning Outcomes (Y)
(Beta=0.410), as well as an indirect impact through increased Motivation (Z)
(Beta=0.192).
The coefficient of determination analysis (R-Square) shows that the Innovative
Methods (X1) and Teacher Competency (X2) variables together are able to explain
56.8% of the variance in Learning Motivation (Z). Furthermore, the combined model
(X1, X2, and Z) simultaneously is able to explain 74.2% of the variance in PAI
Learning Outcomes (Y). This number is highly significant, indicating that the model
proposed in this research (combining method, competency, and motivation) has high
explanatory power to predict PAI learning outcomes.--.

4. DISCUSSION
The most crucial and provocative finding of this research is the rejection of hypothesis 3
(H3), which states that Innovative Learning Methods (X1) do not have a statistically
significant direct influence on Learning Outcomes (Y). This finding sharply challenges the
narrative of "techno-optimism" that dominates much of the current educational literature.
Although studies like Deppeler (2022), Halbusi (2024), & M. Wang (2021) show the
effectiveness of innovative methods in other fields, this research found that in the context of
Islamic Religious Education (PAI), the adoption of sophisticated tools—from Google Forms to
Virtual Reality (VR)—does not automatically guarantee better material comprehension. The
explanation for this phenomenon comes from qualitative data (Teacher B's interview) which
highlights "focusing on the game, not the Fiqh material." Students may enjoy the interactivity
(X1), but their enthusiasm (Z) is distracted by the mechanics of the game, not the substance
of the material.
Conversely, the acceptance of hypothesis 4 (H4) with a strong coefficient value (Beta=0.410)
confirms that Teacher Competency (X2) has a solid direct influence on Learning Outcomes
(Y). This aligns with the observation of Teacher C who was able to achieve high learning
outcomes only using a whiteboard and marker, but supported by deep pedagogical
(contextualizing inheritance law) and spiritual competency. This finding reinforces the thesis
of Muhith (2021) and Samad (2023) that the human factor (the educator) is far more
determining than the tool factor (innovative methods). It is also consistent with the focus of
Assyfa Journal of Islamic Studies (AJIS) on "the role of the teacher" as the main pillar,
affirming that investment in teacher competency development (X2) provides a more certain
impact on learning outcomes (Y) compared to fragmented investment in technology (X1).
A deep reflection on the H3 finding (X1 -> Y rejected) leads the discussion to the second key
finding: the confirmation of Learning Motivation (Z) as a full mediator in the relationship
between Innovative Methods (X1) and Learning Outcomes (Y). This is the theoretical core of
this research. The rejection of H3 (direct effect) and the simultaneous acceptance of H1 (X1 > Z) and H5 (Z -> Y) prove that the X1 -> Z -> Y path is the only valid route. In other
words, innovative methods are useless if they fail to generate intrinsic motivation. The
Student Focus Group Discussion (FGD) explains this perfectly: games (X1) that are "unfair" or
"complicated" actually reduce motivation (low Z) and fail to increase results (Y). Conversely,
games that create "curiosity" (high Z) successfully encourage learning (Y). This indicates that
the value of an innovation (X1) is not in its sophistication, but in its ability to ignite the
psychological aspect (Z) of the student. This finding empirically validates and expands
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Mukaromah’s (2020) research which found a correlation between online learning and
motivation but had not tested its impact up to learning outcomes. This research fills that gap
by proving that motivation is not an end goal (as in many gamification studies) but an
absolute bridge that every method intervention (X1) must cross to impact learning outcomes
(Y).
Furthermore, the discussion turns to the most solid variable in this model: Teacher
Competency (X2). The finding that Learning Motivation (Z) acts as a partial mediator in the
X2 -> Y relationship is a finding rich in meaning. This indicates that competent educators
have two paths to improve student learning outcomes, which explains why the average X2
(80.10) is very high and its influence is very strong. The first path is the direct effect (H4
Accepted; Beta=0.410); an educator with high pedagogical competency (Muhith, 2021) is
able to explain complex material (like inheritance) systematically, clearly, and sequentially. In
this path, students may learn and understand (Y) even without necessarily "liking" the
subject (Z). However, excellent PAI educators have a second path, the indirect effect (H2
Accepted; Beta=0.380); they use their spiritual (Samad, 2023) and personality competencies
to inspire, build relevance, and foster students' intrinsic motivation (Z). This generated
Motivation (Z) then provides an additional boost to the improvement of Learning Outcomes
(Y) (H5 Accepted; Beta=0.505). This partial mediation model shows that competent PAI
educators not only transfer knowledge (direct path) but also transfer inspiration (indirect path
via motivation). This is aligned with the mission of AJIS which emphasizes "moral education"
and "role modeling," which go beyond mere cognitive transfer.
Overall, this research successfully addresses the main research gap identified in the
Background: the problem of fragmentation. The total coefficient of determination (R -Square
= 74.2%) indicates that the proposed integrative model has very high explanatory power.
The thesis of this research—that the improvement of PAI learning outcomes is the result of
simultaneous interaction—is proven true. This finding offers sharp criticism of educational
policies that are often fragmented: (1) Policies that only focus on procuring tools (X1), such
as buying smartboards or VR licenses, will fail if not balanced with an increase in teacher
competency (X2) and its impact on motivation (Z). (2) Conversely, policies that only focus on
training teachers (X2) without providing them with adequate innovative tools (X1), will lose
the potential acceleration of motivation (Z) offered by technology. Thus, the novelty of this
research is the empirical proof that the most effective educational intervention is not "Tool
(X1) or Human (X2)", but "Competent Humans (X2), who wisely use Tools (X1), to generate
the Psychological Bridge (Z), in order to achieve Holistic Outcomes (Y)." This is an integrated
model consistent with the spirit of value integration in the Assyfa Journal of Islamic Studies.

5. CONCLUSION
Based on the data analysis and discussion of findings, this research draws several
fundamental conclusions. First, this research proves that the teacher factor (competency) is
the most solid and strongest predictor of PAI learning outcomes, operating through two
paths: a direct pedagogical influence and an indirect inspirational influence through
motivation. Second, innovative learning methods (technology, games, VR) are proven to have
no direct influence on learning outcomes; their influence is purely indirect and entirely
dependent on their ability to successfully generate student learning motivation. Third,
learning motivation is confirmed as a crucial key mediator variable, serving as the bridge that
must be crossed by innovative method interventions and as an accelerator for teacher
competency interventions. The main thesis of this research is confirmed: holistic PAI learning
outcomes (cognitive, affective, spiritual) are not the product of a single intervention, but the
result of a learning ecosystem where competent educators wisely utilize innovative tools to
The Influence of Innovative Learning Methods and Islamic Education Teacher Competency on
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build the bridge of motivation. The practical implication is clear: educational institutions must
stop fragmented investment and switch to a simultaneous approach, which is training
educators (X2) concurrently with the contextual implementation of technology (X1) to
maximize motivation (Z) and learning outcomes (Y).

References
Abdullah, A., & Hasyim, U. A. A. (2023). The Islamic religious education teacherâ€TMs
professionalism in instilling religious studentsâ€TM character. AMCA Journal of Religion and
Society, 2.
An, Z. (2021). Technology-Assisted Self-Regulated English Language Learning: Associations With
English Language Self-Efficacy, English Enjoyment, and Learning Outcomes. Frontiers in
Psychology, 11. https://doi.org/10.3389/fpsyg.2020.558466
Blankesteijn, M. L. (. L. ). (2024). Towards transformative experiential learning in science- and
technology-based entrepreneurship education for sustainable technological innovation. Journal
of Innovation and Knowledge, 9(3). https://doi.org/10.1016/j.jik.2024.100544
Carvalho, A. (2021). Pedagogical innovation in higher education and active learning methodologies –
a case study. Education and Training, 63(2), 195–213. https://doi.org/10.1108/ET-05-20200141
Cholily, Y. M., Darmayanti, R., Lovat, T., & ... (2023). Si-GEMAS: Serious game mathematical
crossword puzzle learning media for students critical thinking ability. Al-Jabar: Jurnal ….
http://www.ejournal.radenintan.ac.id/index.php/al-jabar/article/view/16113
Deppeler, J. (2022). Innovation and risk in an innovative learning environment: A Private Public
Partnership in Australia. European Educational Research Journal, 21(4), 602–626.
https://doi.org/10.1177/14749041211030400
Geletu, G. M. (2022). The effects of teachers’ professional and pedagogical competencies on
implementing cooperative learning and enhancing students’ learning engagement and outcomes
in
science:
Practices
and
changes.
Cogent
Education,
9(1).
https://doi.org/10.1080/2331186X.2022.2153434
Gökçearslan, Ş. (2024). Acceptance of educational use of the Internet of Things (IoT) in the context
of individual innovativeness and ICT competency of pre-service teachers. Interactive Learning
Environments, 32(2), 557–571. https://doi.org/10.1080/10494820.2022.2091612
Gunness, A. (2023). Effect of student responsiveness to instructional innovation on student
engagement in semi-synchronous online learning environments: The mediating role of personal
technological innovativeness and perceived usefulness. Computers and Education, 205.
https://doi.org/10.1016/j.compedu.2023.104884
Gutiérrez-Martín, A. (2022). ICT and Media competencies of teachers. Convergence towards an
integrated MIL-ICT model. Comunicar, 30(70), 19–30. https://doi.org/10.3916/C70-2022-02
Halbusi, H. A. (2024). The Role of Green Digital Learning Orientation and Big Data Analytics in the
Green Innovation-Sustainable Performance Relationship. IEEE Transactions on Engineering
Management, 71, 12886–12896. https://doi.org/10.1109/TEM.2023.3277078
Handayani, F., & Wijaya, A. (2024). The role of Islamic education teachers in forming students’
religious character. AMCA Journal of Religion and Society, 1, 6–10.
Haryanto. (2021). Innovation Media Learning: Online Project-Based Learning (O-PBL) on Drawing
Competence in Automotive Engineering Using Video on YouTube. Journal of Physics Conference
Series, 2111(1). https://doi.org/10.1088/1742-6596/2111/1/012020
Herlina, I. L., Khafidah, W., Prawirosastro, C. L., & Mukaromah, N. (2025). Pendidikan Agama Islam
di Era Digital. Yayasan Pendidikan Hidayatun Nihayah (Penerbit HN Publishing) , 1, 1–228.
Ho, H. C. Y. (2023). Promoting preservice teachers’ psychological and pedagogical competencies for
online learning and teaching: The T.E.A.C.H. program. Computers and Education, 195.
https://doi.org/10.1016/j.compedu.2023.104725
Irham. (2022). Development of the 4C Teaching Model to Improve Students’ Mathematical Critical
Thinking Skills. International Journal of Educational Methodology, 8(3), 493–504.
The Influence of Innovative Learning Methods and Islamic Education Teacher Competency on
Student Motivation and Learning Outcomes. ICHST. Vol 2 (1). 195-206. 2025

ICHS

205

https://doi.org/10.12973/ijem.8.3.493
Latipun, L., Safitri, N. D., & Novitasari, D. R. (2021). Students’ Enthusiasm for Learning During the
COVID-19 Pandemic: Are Muslim Teachers Successful in Their Roles? AMCA Journal of Religion
and Society, 2.
Lubis, M. (2023). Digital learning media in elementary science: stimulating or demotivating? Assyfa
Journal of Multidisciplinary Education, 1, 18–26.
Mei, H. (2024). Artificial Intelligence Adoption in Sustainable Banking Services: The Critical Role of
Technological Literacy. Sustainability Switzerland, 16(20). https://doi.org/10.3390/su16208934
Niyazbekova, S. U. (2022). Innovative Banking Services in the Conditions of Digitalization. Studies in
Big Data, 110, 73–79. https://doi.org/10.1007/978-3-031-04903-3_10
Nurqotimah, S., Setiawan, A., Anwar, M. S., & Anggraeni, A. D. (2022). The relationship between
peer association and interest in learning against student learning outcomes. AMCA Journal of
Science and Technology, 2, 39–43.
Pan, H. Y. (2024). Does the PBL Teaching Strategy Suit Higher Education Students with Disabilities?
Exploring Financial Literacy Education: Based on PjBL and PmBL. Lecture Notes in Computer

Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in
Bioinformatics, 14785, 281–291. https://doi.org/10.1007/978-3-031-65881-5_30

Pandia, W. S. S., Lee, S., & Khan, S. (2024). The fundamentals of Islamic religious education in
inclusive schools meet special needs children’s PAI issues. Assyfa Journal of Islamic Studies, 1,
77–86.
Parno. (2022). Impact of The STEM approach with formative assessment in PjBL on students’ critical
thinking skills. Journal of Physics Conference Series, 2165(1). https://doi.org/10.1088/17426596/2165/1/012044
Peters, S. (2022). Profiles of German early childhood teachers’ pedagogical content beliefs and the
relation to their competencies. Early Childhood Research Quarterly, 58, 47–58.
https://doi.org/10.1016/j.ecresq.2021.08.001
Pozo-Rico, T. (2023). Revamping Teacher Training for Challenging Times: Teachers’ Well-Being,
Resilience, Emotional Intelligence, and Innovative Methodologies as Key Teaching
Competencies.
Psychology
Research
and
Behavior
Management ,
16,
1–18.
https://doi.org/10.2147/PRBM.S382572
Pramasdyahsari, A. S. (2023). Fostering students’ mathematical critical thinking skills on number
patterns through digital book STEM PjBL. Eurasia Journal of Mathematics Science and
Technology Education, 19(7). https://doi.org/10.29333/ejmste/13342
Rohmat, R., Yusuf, M., Fathurrohman, A., & Choirudin, C. (2024). The Influence Of Islamic Parenting
Patterns and Parents Religious Understanding On Childrenâ€TMs Spiritual Intelligence In Muslim
Families In Metro City. Assyfa Journal of Islamic Studies, 2, 117–126.
Rokhman, R. A., In’am, A., & Habibi, I. (2022). Al-Fatihah-based discipline actualisation to shape the
students’ character: Case study at Madrasah Aliyah Negeri 1 Model Bojonegoro, Indonesia.
AMCA Journal of Religion and Society, 1, 1–8.
Setiawan, A., Anwar, M. S., Wardana, M. R. F., & Yambasu, R. A. (2023). The Effect of Differentiated
Learning on Improving Student Learning Outcomes. Delta-Phi: Jurnal Pendidikan Matematika,
1(1), 46–50.
Sihombing, A. A., Fatra, M., Suhaib, A. Q., & Hussain, N. (2023). Textbook assessment and religious
education efforts: how to achieve religious moderation in schools? Atthulab: Islamic Religion
Teaching and Learning Journal, 2, 153–173.
Simonović, N. (2021). Teachers’ Key Competencies for Innovative Teaching. International Journal of
Cognitive
Research
in
Science
Engineering
and
Education,
9(3),
331–345.
https://doi.org/10.23947/2334-8496-2021-9-3-331-345
Song, J. (2020). A review on fundamentals for designing oxygen evolution electrocatalysts. Chemical
Society Reviews, 49(7), 2196–2214. https://doi.org/10.1039/c9cs00607a
Ssemugenyi, F. (2023). Teaching and learning methods compared: A pedagogical evaluation of
problem-based learning (PBL) and lecture methods in developing learners’ cognitive abilities.
Cogent Education. https://doi.org/10.1080/2331186X.2023.2187943
The Influence of Innovative Learning Methods and Islamic Education Teacher Competency on
Student Motivation and Learning Outcomes. ICHST. Vol 2 (1). 195-206. 2025

ICHS

206

Suadi, S., Mukaromah, N., & Darmayanti, R. (2025). Pendampingan Guru Madrasah Diniyah Dalam
Penggunaan Media Pembelajaran Edukatif di Madrasah Diniyah Darul Falah Dusun Batu Putih
Desa Jatirejo. Jurnal Inovasi Dan Pengembangan Hasil Pengabdian Masyarakat , 3(1), 37–43.
Sukackė, V. (2022). Towards Active Evidence-Based Learning in Engineering Education: A Systematic
Literature Review of PBL, PjBL, and CBL. Sustainability Switzerland, 14(21).
https://doi.org/10.3390/su142113955
Syawaludin, M., Fajarudin, A. A., Bahiyyah, K., Fathurrohman, A., & Mukaromah, N. (2025).
Efektifitas Upgrading Skill Bahasa Arab di Madrasah Tsanawiyah KHA Wahid Hasyim Bangil.
Tarbawi: Jurnal Studi Pendidikan Islami, 13(1), 1–11.
Tacconi, G. (2021). Development of pedagogical competencies of the vocational teachers in Italy and
Lithuania: implications of competence-based VET curriculum reforms. European Journal of
Training and Development, 45(6), 526–546. https://doi.org/10.1108/EJTD-03-2020-0041
Tsybulsky, D. (2021). Project-based learning in science-teacher pedagogical practicum: the role of
emotional experiences in building preservice teachers’ competencies. Disciplinary and
Interdisciplinary Science Education Research, 3(1). https://doi.org/10.1186/s43031-021-00037-8
Tweeten, J. (2023). Design-based Research Method in PBL/PjBL: A Case in Nursing Education.
Interdisciplinary
Journal
of
Problem
Based
Learning ,
17(2).
https://doi.org/10.14434/ijpbl.v17i2.37740
Vedianty, A. S. A., Lestari, A. S. B., Rayungsari, M., & Darmayanti, R. (2024). Development of GABUT
Media Using Critical Thinking Ability Indicators of High School Students in Learning Mathematical
Composition Functions. Numerical: Jurnal Matematika Dan Pendidikan Matematika , 8(2).
Wang, M. (2021). Green process innovation, green product innovation and its economic performance
improvement paths: A survey and structural model. Journal of Environmental Management, 297.
https://doi.org/10.1016/j.jenvman.2021.113282
Wang, X. (2024). Relationships between Self-Efficacy and Teachers’ Well-Being in Middle School
English Teachers: The Mediating Role of Teaching Satisfaction and Resilience. Behavioral
Sciences, 14(8). https://doi.org/10.3390/bs14080629
Zhang, L. J. (2023). Predicting Teaching Enjoyment from Teachers’ Perceived School Climate, SelfEfficacy, and Psychological Wellbeing at Work: EFL Teachers. Perceptual and Motor Skills,
130(5), 2269–2299. https://doi.org/10.1177/00315125231182269
Zia, S. (2022). Celector®: An Innovative Technology for Quality Control of Living Cells. Applied
Sciences Switzerland, 12(19). https://doi.org/10.3390/app12199967

The Influence of Innovative Learning Methods and Islamic Education Teacher Competency on
Student Motivation and Learning Outcomes. ICHST. Vol 2 (1). 195-206. 2025

ICHS