The Collaborative Effort and Efficiency of Inquiry-Based Learning: Effect on the Teacher Performance – The Role of Student Performance

This study investigates the effect on the teacher’s performance of collaborative effort and efficiency of inquiry-based learning. It also determines the impact of the mediating role of student performance. The research framework was constructed based on the unified technology acceptance and use of technology theory. A quantitative analysis was done with surveys to collect primary data from the teacher and lecturers of Malaysia. The researcher used a Likert scale of 7 to evaluate elements of the building. This study focuses on the top 10 public university students in Malaysia. The universities are University Malaya (UM), University Kembangan Malaysia, University Putra Malaysia (UPM), University Since Malaysia (USM), University Technology Malaysia (UTM), Universiti Utara Malaysia (UUM), International Islamic University Malaysia (IIUM), University Technology Mara (UiTM), University Malaysia Perlis (UniMap), and University Tun Hossain (UTHM). Finally, researchers selected the total number of students, 368,881, which is the population of this study. Using systematic random sampling with an interval, researchers sent students an electronic link to respond to a Google Doc questionnaire. This is a unique study in the field of teacher performance that used a diverse and necessary variable known as teaching pedagogy. Therefore, it uniquely integrates leading pedagogy variables into teacher performance. The result of this study helps to meet the education qualification requirement (EQR), and the newly acquired knowledge from this study may help spur the development of the education sector. In addition, it may provide an extensive understanding of making government policies for educational institutions.


INTRODUCTION
Student activeness is a significant factor in teacher performance (Moybeka et al., 2023). Research explained that more proactive students have critical questions and need more examples and discussion during the lecture (Lee, et al., 2023;Saqr et al., 2023). Likewise, another study revealed that quality students asked logical questions and preferred various instances to their study to understand the topic leading the course to learn more about it (Jia et al., 2023. Research indicates that only regular and quality students have the most difficult questions during lessons (Antonietti et al., 2023). To clarify the query, the lecturer needs solid ground for a topic, or the subject, which is a teacher's or lecturer's continuous improvement (Howard, 2023;Sandberg & Fröjdendahl, 2023). A finding mentions that only poor and average students need an extension of assignments and have fewer questions leading to less progress in a lecture or teacher (Sloan et al., 2020). Although, teacher performance is directly impacted by students' critical queries and their expectations (Rusticus et al., 2023). Student success gains are favourably associated with teaching experience throughout a teacher's career (Reeves et al., 2022).
Although the aforementioned studies contributed significantly to developing and improving teacher's performance, a few factors are not yet incorporated . One of the factors is a collaborative effort that reveals the fundamentals of doing things united by a student. This applies to the student's collaboration, hardship, and dedication to their education. These are key roles of students and needful action for success in life; therefore, they are imperative as variables in this study.
The efficiency of inquiry-based learning is not defined as the teaching technique process (Abdul et al., 2023). It enhances understanding by monitoring students' study, daily education activity, and education tasks; moreover, assignment inquiry has not been studied in teaching pedagogy and teacher performance (Siantuba et al., 2023). Student performance defines the teacher's performance, and this considers the fact that student performance as a mediator has not been identified yet (Glover et al., 2023). Student performance reflects the collaboration activity related to teachers' daily education; the collaborative effect and student performance combination construct a strong correlation between learning and the development of interpersonal skills, thinking beyond the shell, and bright ideas that a teacher leads. Moreover, inquiry-based learning and student performances are on a parallel measurement scale that defines the teachers' achievements during their teaching activities during class and has not been covered in teacher performance (Cai & Yang, 2023). Therefore, this study constructs the research questions and objectives based on the identified problem. then, Hartinah et al. (2020) stated that the more the students improve their knowledge capabilities, the higher we rate the teacher's performance. Nevertheless, teachers' performance increases students' thinking, makes them more intelligent, and makes graduates of high calibre (Almulla & Al-Rahmi, 2023). Hasibuan (2022) mentions that teachers' performance is an essential factor that creates attention in their lectures to the student. Determining how a teacher can have a positive influence on the academic performance of their students is done by student test scores (Hakim, 2015). Dian et al. (2022) explained that teachers' performance enhances students learning, grading, individual thinking, and efficiency.

Collaborative Effort
Collaborative effort refers to the interpersonal and intrapersonal skills and competencies we draw upon to solve a problem or make headway toward achieving a shared objective (Bricker et al., 2022;Goldsmith, 2007). Collaborative is an adjective that can describe an endeavor that involves multiple people working together-that is, one in which they collaborate (Bochatay et al., 2022). The phrase "collaborative effort" is frequently used positively to describe two or more people successfully working together on a common goal or project (Patel & Parikh, 2022) because collaborative effort comes from the English phrase collaboration, which means "the effort of working together," or to work together with other people, particularly in the pursuit of academic goals (Assefa, 2022).
To truly engage in a collaborative effort, one must look beyond themselves and make an effort to understand the perspectives of others (Koehler et al., 2022). In addition, collaboration is found only in particular circumstances to do certain things effectively (Garivaldis et al., 2022). This statement indicates that educators' attitudes to doing something more straightforward and efficient are known to have a collaborative effect (Aldriwesh et al., 2022). According to Runtuwene et al. (2022), collaboration effort refers to skills and competencies used by the individual or working together to resolve a problem or make headway toward a shared objective.

Efficiency of Inquiry-Based Learning
The efficiency of inquiry-based learning is one of the ways of learning in the classroom and what teachers are experiencing through their teaching (Liu & Wang, 2022). Problem-solving and experiential learning-that is, problem-solving through open-ended questions-are led by the efficiency of inquiry-based learning (Larsen & Jang, 2022). The efficiency of inquiry-based learning is one of the most effective ways to educate students (Adhami & Taghizadeh, 2022). It reduces boredom in students' learning, which is encouraged at all educational levels (Bush et al., 2022). The efficiency of inquiry-based learning increases attention to the lesson taught. It also expresses a better learning process and experience (Alberto de la Puente Pacheco et al., 2022). Recent research uses evidence  Qiao et al., 2021) to support that efficiency of inquiry-based learning is a process and procedure for educating students in real life and case-solving (Sun et al., 2022).

Student Performance
Student performance is the measurement scale of students' improvement in their education roles (Manz et al., 2022). Higher educational success is typically reflected in a student's GPA, which is usually measured on a performance scale (Aucejo et al., 2022;Gao et al., 2022). Student performance is one of the most critical influences on students' learning and accomplishing the task more quickly (Abu-Eisheh & Ghanim, 2022;Fischer et al., 2022). According to Jokhan et al. (2022), student performance significantly justifies a student's gradual improvement and effectiveness in education learning.
Therefore, we conclude that this variable significantly impacts teachers' performance. Finally, we drive a review focusing on the variable's effect on teachers' performance to see the impact.

Collaborative Effort and Student Performance
The current educational institution/university trend based on learning and teaching inspires collaboration between students and teachers (Costley et al., 2022). A collaborative effort is significant for student performance. Studies show that an average student can perform better when collaborating with brilliant students (Choong et al., 2022). Another study signifies that collaboration is a procedure for student and personal skill development Kousloglou et al., 2023. Likewise, European research defined collaboration as phenomenal to upskilling and boosting student thought toward education (Daou et al., 2022).
Furthermore, collaboration is a tool that breaks the student thinking barrier (Ko et al., 2022). Additionally, some researchers distinguished that collaborative effort can create innovations and provide extensive guidelines for new research (Loughland & Ryan, 2022). A few researchers claim that collaborative effort is the key to a more extensive project and large study (Godbout & Grehaigne, 2022).
The findings in the studies cited in this section led us to form the following hypothesis:

H1:
Collaborative effort influences student performance in the academic industries globally.

Efficiency of Inquiry-Based Learning (EIBL) and Student Performance
The efficiency of inquiry-based learning is highly suggested to increase student performance (Adhami & Taghizadeh, 2022). One study shows that inquiry-based learning can influence student performance (Fischer et al., 2022). The efficiency of inquiry-based learning provides insightful queries about the student activity, an excellent guideline for understanding student performance (Kor et al., 2022). In addition, Liu and Wang (2022) found that the efficiency of inquiry-based learning is significant because it shows student engagement and their capabilities toward teaching and performance. Likewise, a study by Fischer et al. (2022) revealed that inquiry-based learning is critical in identifying students' lack of performance, and Saleh et al. (2022) found that the efficiency of inquiry-based learning provides an insightful efficiency to a student to increase their performance. The findings in these studies led us to form the following hypothesis: H2: Efficiency of inquiry-based learning influences student performance in the academic industries globally.

STUDENT PERFORMANCE AND TEACHER PERFORMANCE
Student performance is essential to enhancing the teacher's performance (Kulikowski et al., 2022).
A study shows that a student's good performance influences teacher performance. It is imperative to emphasize that a collaborative effort toward student learning is directly affected by teacher performance (Shen et al., 2022). Student performance directly influences teacher performance globally in the academic industry (Hafour, 2022). Fischer et al. (2022) posited that inquiry-based learning has an influential ability to enhance teacher performance. A recent study described how teachers' performance depends on student performance (Tran, 2022), and a similar study also revealed that student performance influences teachers' performance (Qiu et al., 2022). Additionally, student performance influences the interaction between the student and teacher (Aucejo et al., 2022). It discloses that interaction between students and teachers has a parallel impact on student performance (Khalil, 2022). In addition, another study found that collaborative projects positively impacted student achievement, thus improving student performance (Saeed & Mohamedali, 2022). Student performance was also a factor in the relationship between the student and teacher (Jerrim & Sims, 2022). There is a correlation between student-teacher collaboration and inquiry-based learning increase and student performance.
Furthermore, Joshi et al. (2022) discovered that the quality of students having more creative questions and proactive attention influences the teacher's preparation for class, extending the performance of a teacher-in-class lecturer. A study by Hsia et al. (2022) described that quality students get more time in class and are more interactive and collaborative, thereby leading to teacher performance through student advancement. However, it is unlikely to get a handful of quality students in class. Still, most quality students insist on better preparation and lecture activity from their teachers, and their demand enhances the teacher's performance (Abu-Eisheh & Ghanim, 2022); therefore, the study demonstrates that students' performance improves teachers' lecture performance.
The findings in these studies led us to form the following hypothesis: H3: Student performance influences teachers' performance in the academic industries globally.

Student Performance as Mediator
According to Cao and Smith's (2023) criteria, a meaningful relationship exists between the predictor variable and the criterion variable, between the predictor variable and the mediating variable, and between the mediating variable and the criterion variable; they contended that no significant overall impact of the predictor variable on the criterion variable was required for mediation (Zhao et al., 2010). These ideas align with others. According to Preacher and Hayes (2008), researchers might theoretically and procedurally explore mediation where a causal relationship between the predictor, mediator, and criterion variables could be constructed. Mediation is a series of triggers in which a second variable influences a third variable. According to Ngah et al. (2022), a potent mediator that is proven by several studies is student performance (SP). SP is a valuable mediating construct. Collaborative effect (CE) acknowledges hardship in teacher performance (TP) through student performance, which influences teacher performance (Chen et al., 2020). After initial use, if students work collaboratively, their performance improves so that the teacher can perform better (Wiyono et al., 2021). The student's understanding and performance enhance the teacher's performance (Rubinstein & McCarthy, 2016). Student group work can improve the process of doing things through collaboration, boosting teacher performance (Lai, 2011). Additionally, student performance is an inspiration for teachers to teach students because they are good at learning, so the teachers are more aware of education, which boosts the teachers' performance (Azmin, 2016).
The efficiency of inquiry-based learning (EIBL) is one of the essential factors that help student performance (Laksana, 2017). When the student becomes good, the teacher needs to prepare them better, leading to improved performance of the teacher (Avsec & Kocijancic, 2014). If the student is not performing well, the teacher is unwilling to upgrade their level (Abdi, 2014). Therefore, EIBL is a fact that leads to teacher performance through the mediation of student performance.
Regarding student performance as a mediator, we formed these hypotheses: H4 A : Student performance mediates the relationship between the collaborative effect and teacher performance. H4 B : Student performance mediates the relationship between efficiency of inquiry-based learning and teacher performance.
This study constructed the research framework in Figure 2.

Measurements
The researcher used a Likert scale of 7, moving from the "Strongly Agree" to "Strongly Disagree," to evaluate elements of the building. This study has four constructs; collaborative effort, the efficiency of inquiry-based learning, student performance, and teachers' performance scale were adapted from previous research (Chao, 2019;Himawan, 2016;Tuan et al., 2005;Venkatesh et al., 2003).

Data Collection
We went to individual campuses to meet the students face-to-face because many studies defined faceto-face study mode as the backbone of the physical university and tertiary education (Alabdulaziz & Tayfour, 2023;Buhl-Wiggers et al., 2023). We also waited for the students to meet at the library's foyer, Figure 2. Research framework entrance, central university lobby, hall, university hot spot, and canteens. Finally, using systematic random sampling with an interval, we distributed the questionnaire for the survey. Additionally, we sent them (respondents) an electronic link via cell phone via WhatsApp and an email to respond to the questionnaire. Hence, we built an online questionnaire using Google Docs. Lastly, we sent the Google Docs links to the interval number (respondents) for the data collection.

Pilot Study
We also ran a pilot test based on the study by Bani-Issa et al. (2023) to determine the reliability of the questionnaire. The questionnaire must pass the pilot test to be improved (Liebenberg et al., 2023). This test is done to find questionnaire errors. A sample size of 30 people is adequate for a pilot study (Byrne et al., 2023). We used the IBM Statistical Package for the Social Sciences (SPSS) program to obtain the Cronbach's Alpha values because Cronbach's Alpha guarantees the dependability of the coefficient or the internal consistency of the scales (Hernández et al., 2023). Furthermore, an alpha value of equal to or greater than 0.8 is highly trustworthy, or greater than or equal to 0.7 is reasonable (Koo et al.,), and greater than or equal to 0.6 reveals poor reliability (Xie et al., 2023). The constructs' dependability results are included in Table 2.

Measurement Model
We followed Henseler et al. (2009) to test the model and used a two-step procedure. Before evaluating the measurement model's discriminant validity, we used Cronbach's alpha and composite reliability to determine whether it was convergently valid.

Outliers, Multicollinearity (VIF)
In this study we used the distance from the Mahalanobis values below 0.001 as outliers (Fino et al., 2023). In this analysis, 13 values were listed as outliers and were consequently excluded. Finally, for further review, 385 cases were included. The multicollinearity statistical approach involves using variance inflation factor (VIF) and tolerance levels (Salim & Ernanda, 2023). The acceptable value of 5.0 and higher is 0.20 or lower with a tolerance level and shows multicollinearity. Table 3 summarizes the product of multicollinearity. Table 3 shows that the VIF was less than 5, and the tolerance was more than 0.20 among the independent variables in this sample. Thus, following Hair et al. (2013), no multicollinearity problems occurred in this analysis.

Reliability, AVE, Discriminant Validity
The indicator's reliability is often called outer loadings, indicating that the latent design explains the indicator's variation. The composite reliability values in this study were acceptable because they were above the threshold of 0.7. In this analysis, the average variance extracted (AVE) values of the latent variables (Table 4) were above the cut-off value (0.50). Henseler et al. (2009) suggested assessing the Fornell-Larcker criterion for detecting discriminative validity. The value of the Fornell-Larcker criterion must be diagonal, and the top value has to be bigger than the lower value. This study finds no discrimination, as shown in Table 5. Table 6 shows that CE directly predicted SP because their relationship was significant (β = 0.608, t = 11.275, and p = 0.000); hence, H1 is supported. Similarly, the relationship between EIBL and SP was significant (β = 0.321, t = 6.093, and p < 0.000); hence, H2 is supported. Additionally, the relationship between SP and TP was significant (β = 0.878, t = 40821, and p = 0.000); hence, H3 is supported.

Structural Model
The t values greater than 1.96 are significant. A p value of 0.05 and below is accepted or supported (Ramayah et al., 2018). The conceptual model for this analysis, including the latent exogenous mechanisms (collaborative effect and efficiency of inquiry-based learning), a mediator (student performance), and the latent endogenous component (teacher performance), is calculated in Figure  4 and Table 6. A structural model showing hypothesized interactions is presented in Table 6. According to Figure  4 and Table 6 The relationship between CE and TP through the mediation of student performance was insignificant, and hypothesis H4A showed that CE indirectly predicts TP because their relationship was significant (β = 0.534, t = 9.942, and p = 0.000). Similarly, the relationship between EIBL and TP through the mediation of student performance was significant (β = 0.126, t = 2.592, and p < 0.10); thus, H4B is supported.

DISCUSSION
A significant relationship was found between CE and SP (H1). The results also indicate that the collaborative effect substantially contributes to student performance in the academic industry (Chen et al., 2020;Rubinstein & McCarthy, 2016;Wiyono et al., 2021). This outcome was similar to the findings of previous studies. The collaborative effect predicts student performance in Malaysia's academic institutions (Abuhassna et al., 2020). The collaborative effect is considered a collaboration of an individual student (Rubinstein & McCarthy, 2016). It enhances the effort of a student and the resultant better understanding of student performance (Wiyono et al., 2021). Therefore, it encourages students are more likely to collaborate for better enhancement of the education industry.
A positive and significant relationship was found between the EIBL and SP (H2) (Abdi, 2014). This finding is supported by the results of previous studies (Avsec & Kocijancic, 2014). Thus, EIBL is a good predictor of SP in academia. Similarly, EIBL impacts SP and creates a more fantastic sensation  Laksana, 2017). Likewise, a study has disclosed that the effect of inquiry on learning is a paradigm for finding the learning improvement on a specific task . It also wholly justifies a particular student or a group of student progress by following inquiry-based learning (Brumann et al., 2022). Inquiry-based learning is a proven element that significantly affects a student's quality assurance. We observed that SP positively and significantly affects teacher performance (H3) (Azmin, 2016; Wiyono et al., 2021). This result suggests that a higher level of student performance boosts teacher performance and the student learning process (Iyamuremye et al., 2022). It also shows that when student performance is visible, it enhances teacher performance (Van Waeyenberg et al., 2022). A possible explanation for this result could be that student performance has developed sustainability in the academic industry (Förster et al., 2022). Student performance is a student's finding that improvement increases teacher performance (Aldrup et al., 2022). While we are discussing student improvement, teacher performance is interrelated (Ma et al., 2022). This study explains student performance's influence on teacher performance . Without student performance, teachers cannot produce their performance (Bellés-Obrero & Lombardi, 2022). Therefore, student performance is an influential variable for teacher performance.
Regarding H4A, this study finds the significance of teacher performance as a mediator in the relationship between collaborative effect and student performance in Malaysia's academic industry (Rubinstein & McCarthy, 2016;Wiyono et al., 2021). A study showed that collaboration and teacher performance are interrelated and are enhanced through student performance (Mendoza et al., 2022;Tang et al., 2022). Likewise, another study disclosed that student performance can influence collaborative effect and teacher performance (Alinejad et al., 2022). Therefore, this study considers student performance as a mediation variable between the efficiency of inquiry-based learning and teacher performance. Regarding H4B, this study supports student performance as a mediator in the relationship between the efficiency of inquiry-based learning and teacher performance (Avsec & Kocijancic, 2014;Laksana, 2017). This finding is consistent with that of a past study. The results are also compatible with a previous study (Yang et al., 2022). Another study showed a significant relation between EIBL and teacher performance, and the results revealed significant improvement in student performance (Sarfraz et al., 2022). Likewise, student performance is an impactful mediation by the collaborative effect and inquiry-based learning (Pianta et al., 2022). Therefore, this study shows that student performance is a decisive mediation variable between the efficiency of inquiry-based learning and teacher performance.

IMPLICATION OF THE STUDy
This research includes direct relations in its theoretical context, which explores its effects on teachers' performance. A direct relationship means it is vital to strengthen teacher performance related to the top public universities in Malaysia.

Theoretical Implication
This empirical study has a significant impact from a theoretical viewpoint developed with Unified Technology Acceptance and Use of Technology. This study is planned to integrate the Teacher Efficacy Theory and Rotter's Social Cognitive Theory from a theoretical standpoint. This theory is used in relationship analysis, taking the performance through the adoption model channel (Tschannen-Moran & Hoy, 2001;Wiyono et al., 2021).
This principle is fitted from the teacher's performance through the adoption point of view. This research is also a new and novel attempt to propagate the idea of teacher performance by Teacher Efficacy Theory and Rotter's Social Cognitive Theory. Moreover, the phenomenon described in this study has been better explained and generalized. An approach based on Teacher Efficacy Theory and Rotter's Social Cognitive Theory better understands the technology and uses associated with an individual teacher's performance. Therefore, this study used the collaborative effect and efficiency of inquiry-based learning to construct a relationship between student performance and teachers' performance.

Methodological Implication
Besides functional and theoretical contributions, several methodological contributions have been established. For the first time, a complex teacher performance model was created, as Hair et al. (2017) proposed that more than four variables were seen as a complex model. We evaluated eight independent variables, one mediator, and one dependent latent teacher performance construct. Thus, this work provided the effect of four independent variables and one mediator simultaneously on the separate construct in the performance through the adoption model. This research has conceptualized teacher performance by integrating different dimensions.

Practical Implication
The findings of this analysis offer valuable insights into reality. This study is significant for academic contributions to universities, the Malaysian government, and other developing countries. Apart from practical implications, multiple aspects apply to this analysis. Teacher performance is also beneficial for Malaysia's education section. Hence, it obtains a significant understanding of this study regarding the relationships between teacher performance and the enhancement of student performance. This is a unique and new study in the field of teacher performance. It also used a very diverse and necessary variable known as teaching pedagogy. Therefore, it uniquely integrates leading pedagogy variables into teacher performance.

CONCLUSION
This research examined the variables affecting student and teacher performance in Malaysia's academic industry. The Malaysian education industry needs to improve its teacher performance because the student is the key element. The following conclusion can be drawn from the results of this study: 1. The collaborative effect and efficiency of inquiry-based learning have significantly influenced teacher performance in the Malaysian education sector. 2. The study also revealed that student performance directly influenced the teacher-performance relationship in Malaysia's education section. It means that the higher the level of student performance is, the higher the teacher's performance is too. 3. The study also discovered that student performance is indirectly influenced by teacher performance in Malaysia's education industry. It demonstrated the interrelation of the predictor, mediator, and dependent variables. The study also found that the predictor variable (CE and EIBL) and teacher performance mediate through student performance.
This research addresses sustainable academic management globally. A societal impact paradigm will be created in the global teaching institution, and a positive quality impact will enhance the quality of future generations globally. In line with the educational vision, it will create a new paradigm and support government plans for education management. In addition, it will provide an extensive understanding of making government policies for educational institutions. Finally, the variable of this study is unique. This new study integrates the performance model Teacher Efficacy Theory and Rotter's Social Cognitive Theory in a single study. This study also incorporates a new mediation and dependable variable, thus making the study novel.

LIMITATIONS OF THE STUDy AND SUGGESTIONS FOR FUTURE RESEARCH
This study focuses on only the top 10 public universities. It also used only four constructs. The respondents were students. Researchers don't use university administration as respondents. Therefore, the scope of the report was to use university students as respondents and all the universities in Malaysia. Costley, J., Courtney, M., & Fanguy, M. (2022). The interaction of collaboration, note-taking completeness, and performance over 10 weeks of an online course. The Internet and Higher Education, 52, 100831. doi:10.1016/j. iheduc.2021.100831 Daou, D., Chakhtoura, M., El-Yazbi, A., Mukherji, D., Sbaity, E., Refaat, M. M., & Nabulsi, M. (2022. Teaching critical appraisal to large classes of undergraduate medical students using team-based learning versus group discussions: A randomized controlled trial. BMC Medical Education, 22 (1)  It would be easy for me to become an education success through the collaborative effect of education success I would find the collaborative effect easier the education success Learning to integrate the collaborative effect is easy for me

Efficiency of inquiry-based learning
The efficiency of inquiry-based learning is one particular way of teaching. (Himawan, 2016) Professional Skill a. Pedagogies The efficiency of inquiry-based learning asks an open-ended question.
The efficiency of inquiry-based learning has various ways of teaching.
The efficiency of inquiry-based learning reduces boredom in education learning.
The efficiency of inquiry-based learning always has some ways to make the students pay attention to the lessons taught.
The efficiency of inquiry-based learning gains a better learning experience.

Students' performance
Student performance would improve education success. (Chao, 2019) Performance expectancy Student performance increases the chances of achieving educational success.
Student performance allows one to accomplish learning tasks more quickly.
Student performance would enhance my effectiveness in education learning.

Teachers' performance
Teachers' performance improves learning and a good grade. (Tuan et al., 2005) Performance goal Teachers' performance increases individual students' capabilities.
Teachers' performance enhances students' thinking that they're smart.
The teacher's performance shows that the teacher pays attention to me.