Abstract
The importance of a person’s belief in their own academic abilities cannot be overstated when it comes to pursuing further education and selecting a career aligned with their studies. This research investigates the influence of family dynamics and background, behavior and values, school experiences and out-of-school experiences on academic self-efficacy (ASE). The study also examines how sub-variables of behaviors and values mediate the development of self-efficacy. The research employs a quantitative cross-sectional survey with a convenience sample of 350 intermediate students from various academic domains. The data analyzed using Smart PLS 4 software, revealed that students’ behaviors and values, as well as their out-of-school experiences have a significant impact on the development of self-efficacy. All variables related to behaviors and values show a significant positive impact, except for decision-making skills, which have no significant effect. However, the indirect influence of technology is also noticed. On the other hand, most background factors and school experiences have no direct influence on ASE. This study offers valuable insights into the multifaceted factors that play a crucial role in family education, teacher education, and career counseling. Additionally, it provides a foundation for future research in this area and contributes to the understanding of adolescents; self-efficacy in academic domains.
Plain language summary
Believing in academic abilities is crucial for education and career choices. This study looked at how family, behavior, values, and out-of-school experiences influence students’ belief in themselves (academic self-efficacy). It involved 350 students from different academic fields. The results showed that positive behaviors, values, and out-of-school experiences have a significant impact on self-efficacy. However, background and school experiences had less direct influence. This research offers valuable insights for education and career counseling, helping us understand how students’ confidence in academics develops.
Keywords
Introduction
It is the belief that students can maximize their Academic Self Efficacy (ASE) by putting psychological effort with the help of their family, peers, and teachers in an educational setting (Bandura, 1997). Academic self-efficacy includes believing in learning efficacy, self-regulatory efficacy and academic achievement (Bandura, 2012, p. 25; Sheu et al., 2018, p. 4). This significantly impacts their career success and academic output (Caprara et al., 2008; Caliendo et al., 2023; Charleston & Leon, 2016; Cheng, 2020; Griffiths et al., 2021; Maczulskij & Viinikainen, 2023; Martins et al., 2018; Sheu et al., 2018, p. 4). In a broader sense, ASE refers to beliefs about one’s ability to perform particular educational and career behaviors (Lent et al., 1994; Sheu et al., 2018, p. 4). Since ASE is considered a major impact of student learning in the 21st century, identifying the factors influencing students’ self-efficacy is a major concern for researchers and educators (Sheu et al., 2018; Van Dinther et al., 2011). This research focuses on recognition of factors nurturing student self-efficacy.
Exploring Academic Self-Efficacy (ASE) is of the utmost importance for intermediate-level students in Pakistan as it sheds light on various phenomena that impact their educational journey, providing valuable insights into students’ levels of interest, persistence and performance in their academic fields (Hilts et al., 2018; Lent et al., 1994; Locke et al., 1984). Understanding self-efficacy helps address important questions, such as why students experience a decline in their performance (S. Iqbal et al., 2021; Khan et al., 2020; Siddiqui et al., 2020a), exhibit reduced interest in their educational domains (Amir-ud-Din et al., 2021), are indecisive about further academic or career goals (Zahoor & Mahmood, 2023), why they think to change their specialization with the transition to higher grades (Asghar & Ajmal, 2022) or discontinue their education before pursuing higher education (Amir-ud-Din et al., 2021). A student’s self-efficacy can provide meaningful insight into their decision to pursue further education and relate to a career path.
Not limited to this, the knowledge of self-efficacy can help to analyze and respond to macro-level problems such as unemployment that more than 31% young educated youths are facing in Pakistan (Tribune, 2022). Self-efficacious individuals can be predicted to show better contribution in the market, the research is evident in entrepreneurship domain, highly self-efficacious have appeared better in risk-taking, innovation and proactiveness (Martins et al., 2018; Maczulskij & Viinikainen, 2023), thus it is crucial to examine self-efficacy and how it is developed.
Primarily Bandura’s Socio Cognitive Theory (SCT) postulated that there are four sources of self-efficacy: (a) personal performance accomplishments (i.e., successes and failures), (b) verbal or social persuasion, (c) vicarious learning (i.e., observation of social models), and (d) emotional states (i.e., anxiety; Bandura, 1986). Several empirical studies have examined existing factors, added other factors, or did not endorse the application of already proposed factors in their social and cultural contexts. As a result of Bandura’s concept, Lent et al. (1996) empirical studies in mathematics education concluded that the model lacks validity through vicarious learning. In order to establish the validity of the model, the authors divided vicarious learning into two factors (a) adult modeling and (b) peer modeling and their findings were positive and significant. Meta-analysis by Sheu et al. (2018) revealed that the direct connection of vicarious learning to self-efficacy were negative, suggesting that it may act as a moderating variable. It was found that when vicarious learning was associated with personal performance accomplishments, social persuasion, and physiological states and responses, the results were positive and significant with a high effect size. The meta-analytic review suggested that personal input that is, gender, race, disability, health status, and pre-dispositions all influence learning experiences and self-efficacy.
According to further research by Bernacki et al. (2015); Klassen (2004), self-efficacy is not always related to past performance or prior mastery, but rather to students’ engagement with different learning tasks and their relevance in real life situations. Similarly, the research has further elaborated that teacher pedagogy, an enabling learning environment, clear learning goals and appropriate learning resources are useful to raise self-efficacy (Koh & Frick, 2009; Kristianto & Gandajaya, 2023; Mohammadi et al., 2020). The research also suggests that self-efficacy is nurtured through personal behaviors (Mohammadi et al., 2020; Schunk & Dibenedetto, 2021), support from mentors and parents and student own interests (Bonitz et al., 2010; Charleston & Leon, 2016). Moreover, individuals’ family background, school environment and out-of-school engagement are additional factors affecting student self-efficacy (Cheng, 2020; Liu et al., 2019b; Phan et al., 2020; Shim, 2018; Simpkins et al., 2019; Yang & Tu; 2020; Zhou et al., 2020).
As a theoretical stance, researchers interpret that ASE is influenced by multiple factors that shape and/or reshape students’ perceptions, decisions, and actions as a result. The contextual variance in determining self-efficacy invites researchers globally to study in their specific contexts (Bandura, 1997; Gebauer et al., 2020), however very limited research has been done in developing countries, like Pakistan. This study examined the factors affecting self-efficacy in the context of a developing country. Most of the prior studies on intermediate-level students are based on exploration of status of their academic performance and their further academic goals. The results have shown decline of students’ performance (S. Iqbal et al., 2021; Khan et al., 2020) and indecisiveness on future planning (Zahoor & Mahmood, 2023). Prior literature however generated the factors impacting students’ choices for academic domain in further education or career (Asghar & Ajmal, 2022) and provided that the perceived command over the subject (an aspect of self-efficacy) is a contributing factor, yet no study has found how self-efficacy is nurtured. Though researchers explored the relationship between Extra-curricular activities (ECA) and academic performance (Muhammad et al. 2022; Rahman et al., 2021; Rathore et al., 2018; Valentine et al., 2002), the connection between ECA and ASE has not been explored yet. In addition to this, no prior study aimed at examining the role of community, safety, direct and mediation effects of students’ problem-solving skills, independent learning skills, hobbies and technology. This study has developed a framework suggesting students’ holistic experiences contribute to the development of ASE. The study offers insight into how students perceive environmental influences in support of their academic learning and growth. This insight becomes the basis for research and reflection on researchers’ education and counseling practices.
Literature Review
In accordance with the literature review, the following paragraphs and Figure 1 show the close relationship between students’ demographics, family involvement, school/college experiences, and out-of-school experiences, as well as their behavior, values and ASE.
Conceptual framework of the study.
Family Dynamics and Background
This section highlights students’ socio-economic status, family involvement, parental education and health.
Impact of SES can be predicted as low-income parents can rarely afford schools that provide quality education and opportunities, this impacts children’s academic confidence (Sandsør et al., 2023; Yeung et al., 2022). Though, a piece of literature has noticed that poor SES students can achieve high if they receive quality schooling (Abenawe, 2022; Liu et al., 2019a). However, despite the effective schooling the effect of parental income appears to have an adverse impact on students’ achievement (Sandsør et al., 2023) and the achievement gap increases with the students’ transition to upper grades (Sandsør et al., 2023). Socio-Economic Status (SES) impacts children’s educational desires and career choices (Afzal et al., 2023). Pupils from strong social classes have above average qualifications (Aina et al., 2022; Song & Tan, 2022).
Parents’ education is also considered important factor. Research shows that educated parents are able to help their children do better in their homework which leads to positive emotions for subject related tasks (i.e., decreased anxiety for subject) and enhance confidence for performance (DiStefano et al., 2023). Much literature highlights the role of parents’ education in children’s academic uplift (Krishnan et al., 2023; Kwarteng et al., 2022; Z. Li & Qiu, 2018; Ma et al., 2022). Research also indicates that parents with lower socioeconomic status can cultivate a positive learning behavior of children through their own educational participation (Z. Li & Qiu, 2018; Şengönül, 2022) and it can conclude that parental education directly influences ASE (Han et al., 2015, p. 6; Z. Li & Qiu, 2018; Romeo et al., 2022). This is by corresponding expectations, opportunities and support from either themselves or availing from significant others such as adults/peers in the face of challenges (Han et al., 2015; Romeo et al., 2022).
Additionally, the role of family involvement is seen to have a noteworthy connection with students’ academic progress (Jeynes, 2022). Children’s learning capabilities are shaped by their families’ interest in their education, their high expectations, and the support they receive from their parents (Deci & Ryan, 1985; Hektner, 2001; Jeynes, 2022; Şengönül, 2022; Tan et al., 2020). Research shows that collaboration with parents enables students to overcome various problems including social, emotional and academic (Guay, 2022). In order to shape self-concepts, family members require supportive behaviors such as involvement, significant activities, and structure (Guay, 2022). It is evident that children who receive quality parental support feel relaxed, joyful, intimate, coordinated, and emotionally synchronized; these children often meet expectations and show appropriate roles (DiStefano et al., 2023).
However, academic achievement is also dependent on physical well-being. Illness leads to school absenteeism in school. This is what students missed-out classroom instructions or review sessions that negatively impact academic outcomes (Keppens, 2023; Klein et al. 2022; Luo et al., 2023; Matingwina, 2018) including self-efficacy (Santibañez et al., 2021). The concept of health is evolving overtime, and need to be explored (Matingwina, 2018). This study intends to find the impact of health issue on ASE. The following hypotheses are generated.
H1: High-Economic Status has a significant positive impact on ASE.
H2a: Father higher Education has a significant positive impact on ASE.
H2b: Mother higher education has a significant positive impact on ASE.
H3: Family Involvement has a significant positive impact on ASE.
H4: Good Health has a significant positive impact on Academic Self-Efficacy (ASE).
School/College Life Experiences
Other indicators of ASE include school experiences such as active class participation, teachers’ high expectations, teachers’ feedback, peer learning, career counseling, extra-curricular activities, school safety and past achievement.
Literature shows that participation in classroom activates students’ learning mechanisms (Kristianto & Gandajaya, 2023; Mohammadi et al., 2020) and contributes to course understanding (Jansen et al., 2017; Kristianto & Gandajaya, 2023; Pintrich et al., 1991). Significant activities, class structure such as group work and teachers’ individualized support impact learning outcomes and self-efficacy (Charleston & Leon, 2016; Kristianto & Gandajaya, 2023; Mohammadi et al., 2020; Yıldızlı & Saban, 2016).
The significance of peer learning is highlighted in literature. Peers are a necessity to fulfill psychological needs such as competence, autonomy and relatedness, as found in the meta-review (Guay, 2022). There are many studies showing that peer collaboration helps develop higher order thinking abilities such as problem solving, critical thinking, and creativity (Blaskova & McLellan, 2018; Hwang et al., 2018; Kristianto & Gandajaya, 2023; Schunk & DiBenedetto, 2021). Peer influence can shape and reshape academic self-concept (Pintrich et al., 1991). This is because during peer-learning students get a chance to listen to the views of group members, exchange different opinions and positive criticism, learn how to solve and overcome conflicts, learn to ask meaningful and clarify questions (Bećirović et al., 2022). In addition, peer-pressure can lead to personal responsibility and motivation for high achievement (Bećirović et al., 2022).
Research has investigated the positive influence of teachers’ expectations on students’ self-perceptions (Demie, 2022; Friedrich et al., 2015; Trusz, 2018). In contrast, when teachers communicate low expectations through harsh reprimands, express biases, or fail to answer students’ questions, students become passive about learning (Demie, 2022; Johnston et al., 2021). Qualitative research found that teachers’ expectations vary for different ethnic groups of students (Demie, 2022). The marginalized students receive less regards/praise in their class performance, are frequently disciplined, and even show a consistent decline in their academic progress compared to their counterparts (Demie, 2022).
Along with high expectations, teachers’ feedback is equally significant, since its focus lies on diminishing the gap between current and expected performance, which means that it helps students develop skills to meet more realistic expectations (Hattie & Timperley, 2007). Informative and autonomous feedback enhances self-efficacy (Wisniewski et al., 2020). The effects of feedback would be negative or low when feedback is controlling, negative and uninformative, feedback administered in controlling takes away responsibility from students for regulating themselves (Wisniewski et al., 2020). Other studies expanded that feedback will be potential when (a) helps students to engage in self-talks (b) encourages autonomy, such as by telling students the success is the result of their own hard work and good learning strategies –this can be managed by the students (c) feedback based on the information acquired about students’ learning needs (Fatima et al., 2022; Granberg et al., 2021). However, the effects of feedback can also be dependent on learners’ ability to utilize that feedback (Zhang & Hyland, 2022) as the positive use of feedback can enhance ASE (Zhang & Hyland, 2022)
Furthermore, career discussions organized by educational institutes may also influence ASE (Deng et al., 2022; Parzych et al., 2023). Research indicates that career discussions (i.e., discussions on how the academic world will benefit students’ career development) help improve academic achievement (Legum & Hoare, 2004; Parzych et al., 2023; Stipanovic et al., 2017). Studies found career services enhanced students’ sense of career and academic self-efficacy by increasing their motivation to complete school, willingness and interest to enhance curiosity, and acquired knowledge and abilities that are useful to accomplish mission (Deng et al., 2022; Santilli et al., 2020; Stipanovic et al., 2017).
Also, educational institutions reshape pupils’ ASE through offering Extra-Curricular Activities (ECA). The connection of ECA with positive academic outcomes is revealed by several studies (Buckley & Lee, 2021; Muhammad et al., 2022; Rahman et al., 2021; Rathore et al., 2018; Valentine et al., 2002). The linkage is suggested in a way that, students who participate in ECA exhibit physical fitness and better engagement in classroom, improve attitude toward studies, maintain discipline and ensure class attendance (Rathore et al., 2018), persist motivation and develop collaboration and leadership behavior (Ahmad et al., 2019; Buckley & Lee, 2021).
Nevertheless, participation in school-organized activities is largely influenced by a safe environment. School safety is an influential factor (Cornell, 2021; Edwards et al., 2021). Students who live in a hostile environment such as harassment, threats, lack of discipline, or conflicts may be absent from class and be negatively affected by their learning behaviours (Edmondson et al., 2016; Maxwell, 2016, p. 17). In an unsafe environment, students are less willing to speak or ask for help (Edmondson et al., 2016; Flensner & Von der Lippe, 2019).
Moreover, students who maintain their academic progress in previous grades continue to maintain self-efficacy (Smith & Hirschl, 2022; Van Dinther et al., 2011). In contrast, students, whose academic records are sub-standard, remain unsure about the outcome of their efforts in subsequent grades (Klassen, 2004; Wessel et al., 2008). Even for young adults from low-income communities, past accomplishments determine their career interest, their commitment to learning, and their readiness to accept new challenges (Peterson, 1993; Tinto, 1975) and the readiness to accept new challenges (Smith & Hirschl, 2022).
H5: Past achievement has a significant positive impact on ASE.
H6: Class participation has a significant positive impact on ASE.
H7: Peer-learning has a significant positive impact on ASE.
H8: Teacher High expectation has a significant positive impact on ASE.
H9: Teacher feedback has a significant positive impact on ASE.
H10: Career discussion has a significant positive impact on ASE.
H11: Safety significantly and positively influences ASE
H12: Extra-curricular Activity significantly and positively influences ASE
Out-of-School Experiences
Out-of-school activities include community interaction, time spend with technology, and celebrating hobbies.
Within the community, peers exchange ideas, share values and social concerns and see volunteering as a way of making a difference (Jones & Hill, 2003). Time spent with peers may influence social learning and well-being (Berry et al., 2007; Hektner, 2001). Discussions with peers/adults lead to co-construction of knowledge which benefits students in the academic world and positively contributes to self-concepts such as self-esteem and self-efficacy (Valentine et al., 2002). Also, pupils get the opportunity to observe the person similar to their field (major of study) and their accomplishments; this can influence their levels of confidence, motivation and efforts (Bandura, 1997; Charleston & Leon, 2016). Research suggests that pupils develop self-concepts through their interpretation of appraisals by others, for youngsters mostly rely on other’s opinion to create their own judgment of confidence and self-worth (Price, 2008, p. 19). They often validate their identity with the evaluations of significant others, among them trusted members in the community are influential who contribute to the development of positive self-image.
In addition to this, technology is one of the emerging factors that play a unique role in adolescents’ development (Dienlin & Johannes, 2022; Yan, 2018). Technology’s implication in education is demonstrated by many studies (Rodriguez-Segura, 2022; Siddiqui et al., 2020a; Siddiqui et al., 2020b). Technology helps students learn at their own pace, and at their own level which is helpful in self-led learning (Rodriguez-Segura, 2022; Siddiqui et al., 2020a). Social and active use of digital platforms has positive effects on well-being (Dienlin & Johannes, 2022). Active use includes communication with friends and family, working on a project, creating content, or learning through videos (Magis-Weinberg & Berger, 2020). Research studies by Hwang et al. (2018); Fitton (2013) revealed that students develop their skills and higher order thinking skills (such as problem-solving skills) with technology. Digital technology’s impact on well-being, however, depends on the focus, unplanned use will have different outcomes (Dienlin & Johannes, 2022). Also, not all the adolescents benefit equally from digital technology. Students who are at risk (exposed to vulnerable society and relationships) can cause online risks (Odgers & Jensen, 2022). A lack of sensitivity to technology may leave negative impacts (Zaheer, 2018).
Other out-of-school experiences involve pupils’ engagement in hobbies since hobbies affect ASE (Griffiths et al., 2021; Valentine et al., 2002). However, there is the need to examine what hobbies link ASE in the context of a developing nation such as Pakistan. This study intends to explore the impact of hobbies as well
H13: Community participation significantly and positively influences ASE.
H14: Technology usage has a significant and positive influence on ASE.
H15: Hobbies have a significant and positive influence on ASE.
Behaviors and Values
Students’ behaviors and values are key to notice when measuring ASE. Career interest (the desire to pursue a career related to the field), problem-solving, decision-making, and independent learning are some of the behaviors and values that are mentioned in the following paragraphs.
Career interest has a significant influence on self-efficacy (Bonitz et al., 2010; Deng et al., 2022; Nauta et al., 2002). Career interest in pursuing a related professions ensures learning commitment (Tinto, 1975, p. 1). Through repeated exposure to interest-relevant activities, individuals gain sense of mastery, which contributes to ASE (Bonitz et al., 2010; Tracey & Robbins, 2005). Students’ career interest determines the development of academic goals that help them persist, manage resources such as time and space (Dweck, 1986; Miller & Brickman, 2004). Interested students ask themselves whether they possess sufficient information and adapt different strategies to address their knowledge gap (Tinto, 1975; Peterson, 1993). These behaviors may include asking questions from expert/teachers/online resources (Liu et al., 2019b). Factors impacting students’ development of career interest are support from family including siblings or cousins and school (Ahmed et al., 2022; Charleston & Leon, 2016; K. Iqbal & Modood, 2023; Ma et al., 2022; Parveen et al., 2022; Stipanovic et al., 2017). They play vital role in offering knowledge of various disciplines and developing vocational interest (Vasilescu et al., 2015).
In addition, independent learning habits impact academic outcomes (Amida et al., 2021; Zhao et al., 2023). In independent learning, individuals assume responsibility for directing, regulating and assessing their learning (Livingston, 2012; Nguyen & Habok, 2022). Their academic efforts are expected to yield success (Amida et al., 2021). Studies also prove that independent learners are self-efficacious and high achievers (Lavasani et al., 2011; Yıldızlı & Saban, 2016; Zhao et al., 2023). The behaviors that represent independent learning such as self-study, goals, planning, and engagement in production of quality tasks (Deci & Ryan, 1985; J. Huang & Benson, 2013; Livingston, 2012; Wei et al., 2022; Zhao et al., 2023). Studies have found the impact of self-study on academic self-efficacy (Abdous, 2019; Mamolo, 2022). An external environment, such as the contribution of the family and classroom participation, may assist independent learning behaviors (K. Iqbal & Modood, 2023; Magnusson & Zackariasson, 2019).
Problem solving is defined as the self-directed cognitive-behavioral process by which an individual, couple, or group attempts to identify or discover effective solutions to specific problems encountered in everyday living (Chang et al., 2004). It is observed that students face a variety of problems, such as loneliness, helplessness, perceived stress related to academic high expectations, lack of management of time and finance and poor social skills (Hitches et al., 2022; C. Y. Huang et al., 2022). Problem solving simultaneously bring the change in problematic situation enhance well-being (Rodríguez et al., 2022) and reduce emotional distress (Chang et al., 2004), the positive emotions support ASE (Badura, 2012). Coping habits reshape positive image of self for instance lead to develop self-goals and missions, however fail to deal with the problems create complexities to developing self-values or goals (C. Y. Huang et al., 2022). Thus problem-solving can be positively linked with self-efficacy of students (Shenaar-Golan et al., 2020; Sun & Lyu, 2022). School environment such as classroom instructions and teacher feedback play a vital role in improving problem solving abilities (X. Li et al., 2022; Williams, 2013; Hwang et al., 2018; Zhou et al., 2020). A meta-analysis found that feedback promotes regulation in students, predicting self-efficacy (Wisniewski et al., 2020). In addition to this, technology also plays a significant role in dealing with multi-dimensional problems students face (Fitton, 2013; Hwang et al., 2018; Magis-Weinberg & Berger, 2020).
Decision making is considered an important behavior require students to choose among various alternatives (Abdullah & Rahman, 2020; Janis & Mann, 1977). Decisions are necessary when students confront problems such as: high pressure of academic success, parental expectations, low academic skills and abilities, academic challenges, time management, mental health problems such as stress aggression, and low-self-esteem due to failure, lack of support from peers, vulnerable neighborhood environment, economic problems. These circumstances need individuals to take decisions (Abdullah & Rahman, 2020; Bergmann & Rudman,1985). Following hypothesis are developed
H16.1: Career interest directly influences ASE.
H16.2: Career interest mediates the relationship between family involvement and ASE.
H16.3: Career interest mediates the relationship between career discussion and ASE.
H17.1: Independent learning behavior directly influences ASE.
H17.2: Independent learning behavior mediates the relationship between family involvement and ASE.
H17.3: Independent learning behavior mediates the relationship between class participation and ASE.
H18.1: Problem solving behavior directly influences ASE.
H18.2: Problem solving behavior mediates the relationship between class participation and ASE.
H18.3: Problem solving behavior mediates the relationship between teacher feedback and ASE.
H18.4: Problem solving behavior mediates relationship between technology usage and ASE.
H19: Decision making (DM) directly influence ASE.
The earlier mentioned literature review presents evidence that Academic Self-Efficacy (ASE) is influenced by a range of factors, including students’ background and family engagement, educational institutions, external elements outside of school, as well as students’ behavior and values. Furthermore, it emphasizes the significant role of external factors in refining individual behaviors and values that are crucial for enhancing academic self-efficacy.
Methodology
Under the positivist paradigm (based on objectivity, standardization, deductive reasoning, and control) this study employs a quantitative cross-sectional survey to identify factors influencing self-efficacy (Creswell, 2013). In order to collect data, a questionnaire is designed (see Table 2) which was developed based on literature reviews and piloted on 163 students. The instrument was deemed reliable and valid (see Table A2). The items development process is given below.
Items Development Process
Mixed method approach was used to develop questionnaire items from (a) literature review and (b) qualitative focus group interview.
Phase 1: Literature Review
The items and their constructs were developed by reviewing related literature and prior instruments (see column 2 of Table 2). The review of literature identified four major domains (family dynamics, educational/school experiences, out-of-school experiences, and own behaviors and values).
Phase 2: Focus Group Interview
Two focus group (one for girls and one for boys) interviews were conducted with intermediate-second year students, each group consisted of six students and lasted for a total of 40 min. Research question was: “What factors help you (or a student of your age) to gain academic self-efficacy/self-confidence?”. Data was analyzed through initial, focus and selective coding. Table A1 contains result of the coding.
Phase 3: Development of Items
During this phase, 97 items were developed under 13 factors. This study followed item scripting, item selection and item analysis. Eighty-eight Items were retained after assessment by a senior professor who teaches test design course at graduate and post-graduate level from a well reputed university from metropolis city of Pakistan. In addition, three assistant professors from the department of education in a well-known university with more than 10 years of experience also participated in items analysis. Some items were revised and ensured face and content validity.
Phase 4: Pilot Study and Exploratory Factor Analysis
A pilot study was conducted to identify double-barreled or repeated items and to correct ambiguity or ambiguity in the text. An exploratory factor analysis was performed using 163 completed questionnaires from 167 conveniently accessible participants. During this phase 67 items were retained after exploratory factor analysis. Almost all factors loadings (>0.7), reliability (Cronbach’s alpha > .7) and reliability (composite reliability > 0.7) as well as validity (AVE > 0.5) proved acceptable (Hair et al., 2011). The factor loading and AVE of some variables were above 0.4, but they are also within the acceptable range (Lam, 2012). Table A2 presents exploratory factor analysis results. To ensure no multicollinearity exists, Table A3 with complete cross loading is also provided. Figure 2 shows a summary of the item development process.
Items development process.
The target population of the study is intermediate-second year (Grade-12) students. Research process was started with the identification of those public and private institutes within district south having enrollment of more than 200 students, with the daily average attendance of 30 students in each class. The official permission for conducting the study was sought. A convenience sampling method was used to recruit participants, and an in-person survey method was used to administer the instrument. The data collection was started in Feb-2023 and continued till March-2023. Since the response rate from each college was not very high, the researchers collected the data and finally two private-sector colleges/higher secondary institutes and seven public sector colleges were covered. The number of public and private colleges is selected based on their ratio in District South Karachi. Ethical practices were observed throughout the research process. The students were shared the purpose of research, interested students took part from each college. Though 23 questionnaires were returned in-completed thus discarded, finally 350 questionnaires were used for analysis.
Since students participated from nine large educational institutions of District South, Karachi, the findings can be generalized to all students of these institutions.
The study measured various factors in the following ways:
Socio-economic status (SES) was determined by examining household income.
Past achievement was assessed through matriculation grades.
Health status was evaluated using two questions: (a) “Did you experience any illness or injury in the last two years?” b. “If yes, how long did it last?”
Parental education was captured by asking: (a) “What is your father’s educational background?” (b) “What is your mother’s educational background?” The Likert scale was utilized, where 1 represents no education, 2 denotes primary education, 3 signifies secondary education, 4 stands for higher secondary education, and 5 indicates university education.
Participation in extra-curricular activities (ECA) was measured using the question: “Do you take part in ECA offered by your educational institution?” A 3-point Likert scale was used: 1 for never, 2 for rarely, and 3 for mostly.
The impact of technology was assessed through the question: “While using technology, how many hours per week, on average, do you spend engaging in educational activities, such as watching educational videos, using websites, communicating academic concerns with peers or teachers, and solving quizzes?” A Likert scale with values ranging from 1 to 6 was employed, representing different time intervals. 1 denoted less than an hour, 2 indicated 1 to 5 hr, 3 stood for 6-10 hr, 4 represented 11 to 15 hr, 5 meant 16 to 20 hr, and 6 indicated more than 20 hr.
Additionally, the study categorized students’ hobbies into four groups: (a) Sports/active activities (e.g., indoor and outdoor games) (b) Artistic/creative pursuits (e.g., gardening, traveling, painting, handicrafts, dancing) (c) Academic/personal development interests (e.g., reading, technical skills, emerging technology) (d) Baking food This categorization approach was similar to the one employed by Griffiths et al. (2021).
Quantitative Data Analysis
This study employed partial least squares structural equation modeling (PLS-SEM). PLS-SEM algorithm was calculated using path model at standardized and default system. Boot-strapping was performed on 5,000 samples with parallel processing. Test type used was two-tailed at a significance level (0.05). Sig (p < .05) was calculated to reject the null hypothesis.
Demographic
Data were collected from students of private and public sector colleges. Participants’ mean age was17 to 18 years. The study recruited students (boys and girls) from different disciplines such as Pre-Medical, Computer Science, Pre-Engineering, Commerce, and Arts (see Table 1).
Sample General Demographic Information.
Outer Model Measurement
The outer measurement model encompasses the evaluation of reliability and validity of data (Hair et al., 2011). Reliability is measured to ensure the variables’ internal consistency while validity confirms that the constructs indeed measure what they are intended to measure.
Reliability Testing
Cronbach’s alpha and composite reliability (CR) were used to determine reliability. Table 3 shows composite reliability values for each construct. The majority of Cronbach’s alpha values and composite reliability values are higher than .7, indicating a very high level of reliability. Only one indicator “decision making” has Cronbach’s alpha of .658; however, its CR is over .7, which qualifies it for further analysis (Raharjanti et al., 2022; Hair et al., 2011).
Validity Testing (Convergent Validity)
Convergent and discriminant validity were used to evaluate the study validity. Convergent validity examines the degree to which the items collectively measure the relevant concept and also indicates the correlation between the items within their respective constructs (Hair et al., 2011). Average Variance Extracted (AVE) was employed to assess convergent validity. The AVE values should be equal to or greater than 0.5, and the items should have loadings above 0.5 on their respective constructs (Hair et al., 2011). Items with loadings below 0.5 were removed by researchers. The AVE values and loadings for all items fell within the recommended range, as shown in Table 2.
Reliability Testing and Convergent Validity.
Note. ASE = Academic Self-efficacy; CI = career interest; IND = Independent behavior; PS = Problem solving; FI = family involvement; CP = class participation; PL = peer learning; TE = teacher expectation; TF = teacher feedback; CD = career discussions; SF = safety, CoP = community participation; DM = decision making.
Discriminate Validity
The discriminate validity of a construct is a measure of the extent to which items of one construct measure a different concept from another one (Hair et al., 2014). Discriminate validity was established using the Fornell and Larker criterion (Henseler et al., 2015). Fornell and Larker criterion suggests that constructs should exhibit more variance with their own items than other variables. The values in a diagonal line should be greater than the inter-construct correlation (Hair et al., 2011). Table 3 confirms Fornell and Larker’s discriminating validity method.
Fornell-Larcker Outcomes.
Inner Measurement Model and Hypothesis Testing
After evaluating the outer measurement model, the inner model is examined through PLS-SEM (Partial Least Squares- Structural Equation Modeling) in Smart PLS 4 (Ringle et al., 2015). The measurement was estimated and hypotheses were tested using bootstrapping (Henseler et al., 2009). It involves resampling and creating sub-samples of at least 5,000 from the original data (Hair et al., 2014).
Predictive Relevance of the Model
The quality of an inner model depends upon how better it predicts endogenous constructs (Hair et al., 2014). For the assessment of the inner model, the primary criterion is examining the coefficient of determination (R2), adjusted R2 and cross-validated redundancy (Q2) (Hair et al., 2014; Henseler et al., 2009). The predictive power of the variables is evaluated through the coefficient of determination (R2) and adjusted R2.The values of R2and adjusted R2 higher than 26% are considered substantial (Hair et al., 2014). Results of R2 and adjusted-R2 are presented in Table 6. R2 values and adjusted R2 values for both the endogenous constructs are more than 26%, thus confirming model fitness and supporting better prediction quality.
Cross-validated redundancy (Q2) is another option for checking model accuracy. Q2 assesses the predictive relevance of the inner model (Hair et al., 2014). PLS predict method is used to measure the Q2. The value of Q2 should be greater than zero. Table 4 shows the vales of Q2, hence confirming the model fitness as all values are greater than zero.
Predictive Power of Constructs.
Note. CI = Career Interest; IND = Independent behavior; PS = problem Solving; ASE = Academic self-efficacy.
Hypotheses Testing
The research study comprises a total of 19 hypotheses. To accept these hypotheses, the significance value of p < .05 is utilized. The findings of the hypotheses testing are presented in Table 5. Based on the results, it is evident that none of the variables related to students’ background have a significant direct impact on ASE. Consequently, all hypotheses examining the relationship between students’ background and ASE are rejected (H1, H2a, H2b, H3, & H4). Similarly, the majority of hypotheses concerning school/college experiences are also rejected due to their insignificant influence on ASE. These include past achievement (H5), class participation (H6), teachers’ expectations (H8), teacher feedback (H9), career discussions (H10), and extra-curricular activities (H12). Only school safety (H11) and peer learning (H7) exhibit a direct positive and significant impact on ASE. On the other hand, various factors pertaining to out-of-school experiences, such as hobbies (specifically cooking; H15.1) and personal/academic development pursuits (H15.4; see Table 6), community participation (H13), demonstrate a positive and significant effect on ASE. Although technology usage (H14) does not display a direct effect, its indirect impact is still significant (H18.4). Another set of factors encompassing individuals’ behaviors and values prove to be significant predictors of ASE, except for decision-making (H19). Career interest (H16), independent behavior (H17), and problem-solving skills (H18) exhibit a significant and positive influence on ASE, thereby supporting the respective hypotheses. Furthermore, career interest and independent learning act as potential mediators between students’ background (specifically family involvement) and ASE (H16.2, H17.2). Similarly, career interest is a potential mediator between career discussion and ASE (H16.3). Additionally, independent learning and problem-solving skills fully mediate the relationship between class participation and ASE (H17.3, H18.2). Lastly, problem-solving skills serve as a potential mediator between teacher feedback, technology usage, and ASE (H18.3, H18.4).
Hypotheses Testing Results.
Note. SES = Socio-economic status; ASE = Academic Self-efficacy; CI = career interest; IND = Independent behavior; PS = Problem solving; FE = father education; ME = mother education; FI = family involvement; PA = past achievement; CP = class participation; PL = peer learning; TE = teacher expectation; TF = teacher feedback; CD = career discussions; SF = safety; ECA = Extra-curricular activity at school; COP = community participation; TECH = Technology; DM = decision making.
The Impact of Out of School Experiences (Hobbies) on ASE (Results from Independent T-Test).
Note. Dependent variable Academic Self-efficacy (ASE).
shows significant difference.
Discussion
This study aimed at exploring and describing the factors predicting ASE in students. Our analysis of the study suggests Academic Self-efficacy is a living concept, nurtured over time under the influence of several contextual factors such as family involvement, educational institutions including teacher-student interaction and class participation, safety, community, peers, own values and behaviors, inventions (technology) and hobbies. There are some similarities between the results of the study and existing literature when it comes to determining self-efficacy; the results show direct and indirect impacts of independent variables. However, the study analysis also reveals certain contradictions with previous studies.
Family Dynamics and Students’ Background
The findings support the literature that family’s role is dynamic in developing ASE (as discussed in Hektner, 2001; Tan et al., 2020; Tösten et al., 2017); however, it is important to recognize the mediation effect of students’ motivation and interest in continuing their learning. Even though families have high expectations for their children, ASE will not be shaped unless children’s interest and independence grow. It is also worthwhile to mention here that in the context of this research, family is defined as a group of individuals/relatives sharing one common house. Additionally, the results indicate that family socioeconomic background and parental high education do not appear to contribute positively to the development of ASE. These findings contradict studies in the East Asian context where higher income and parents’ higher education predict better academic outcomes (Han et al., 2015, p. 6; Ma et al., 2022). This suggests that higher income does not meet better educational opportunities and support for children (Aina et al., 2022; Caprara et al., 2008; Z. Li & Qiu, 2018; Song & Tan, 2022). This may be because many parents still have a traditional mind-set with less-expectations from girl child education (Ahmed et al., 2022; Khanam et al., 2022). Students who are interested in education tend to be more influenced by their siblings and/or cousins than by their parents, and they continue education regardless of poverty or illiteracy in their parents (Ahmed et al., 2022). Another explanation is the tuition trend and many parents’ inability to deal with the complexity of modern syllabus at secondary or upper levels of education (Ma et al., 2022; Parveen et al., 2022).
In addition to family roles, students’ health was assessed. Findings showed students’ health status was not connected with ASE. The data revealed that the nature of the illness was short term and seasonal but curable. Perhaps the health illness did not affect their psychological and physical abilities (Mullins et al. 2011), and may not lead to school absenteeism (Keppens, 2023; Klein et al. 2022) and thus the self-efficacy (Santibañez et al., 2021).
Behaviors and Values
It is important to recognize that while considering career interest, as an independent variable, the results show participants who are determined to reach their career aligned with their academic domain are more likely to put effort, motivated toward new learning and open to accepting challenges and manage their time and organize their academic schedule. Our findings confirm that the higher the career interest, the greater the ASE (as shown in Deng et al., 2022).
Additionally, independent study habits contribute equally to ASE development (as found by Amida et al., 2020; Ilyas & Azam, 2022; Zhao et al., 2023). The explanation is that students’ autonomous behaviors such as self-study, goals and planning, employment of strategies and inquisitiveness of production of quality task can enhance their ASE. The similar observations are made in previous studies (Abdous, 2019; Mamolo, 2022; Wei et al., 2022; Zhao et al., 2023). Our findings contribute to the existing literature of independent study in grade-12 education setting in lower-middle income-country.
Another powerful predictor of ASE is problem-solving behavior. This is students’ involvement in identification of problems and use of strategic mechanism to resolve problem. Students may face problems related to emotions, loneliness, helplessness, perceived stress related to academic high expectations, lack of management of time and finance and poor social skills (Hitches et al., 2022; C. Y. Huang et al., 2022). Such problems make lives perplex and halt students’ goals and values and bring threat to individual-self (C. Y. Huang et al., 2022), however, coping with problems enhances well-being (Chang et al., 2004; Rodríguez et al., 2022) and self-efficacy (Shenaar-Golan et al., 2020; Sun & Lyu, 2022).
However, the input of educational institutions to learners’ growth of ASE is dependent upon how well they develop behaviors and values. Since career interest, problem-solving and independent thinking have appeared potential mediators in our study. The results show that class participation and teacher feedback link with ASE in the presence of mediators: independent learning and problem solving behaviour. This suggests that teaching strategies such as asking questions, creating situations ignite learner’s cognitive engagement in the task and reach solution to their problem can substantially increase ASE. Similar viewpoint in found in the study (X. Li et al., 2022). This is due to classroom activities can successfully push learners to analysis, synthesis and reach conclusion or solve the problem (X. Li et al., 2022).
Similarly, results highlight that teachers’ feedback contribute to ASE when students use feedback to solve their problems. Since feedback can be considered for critical reflection on ones’ strengths and weaknesses, and applied to overcome weak areas, inefficient feedback or inability to use feedback positively may risk ASE (Zhang & Hyland, 2022). The results can extend to students’ career success in entrepreneurship domain. The study by researchers have shown that self-efficacy would grow when youths are equipped with problem-solving skills (as also noticed by Caliendo et al., 2023) which further shows its impact on entrepreneur orientations such as risk-taking, innovativeness, proactiveness (Martins et al., 2018; Maczulskij & Viinikainen, 2023) and entrepreneurship success that is, probability of being an entrepreneur, and outstanding performance (Maczulskij & Viinikainen, 2023). The findings have potential to contribute to gap in knowledge within entrepreneurship education and career.
The same connotation appears when observe relationship between school-based career discussion and students’ ASE. The results show that career discussion is effective that lead to increased career interest, since career interest is a strong mediator between career discussion and ASE. The results are consistent with prior literature (Santilli et al., 2020; Stipanovic et al., 2017). This is due to successful career discussion offer guidance for students to invest in career related activities and how to feel learners more motivation toward career (Santilli et al., 2020; Stipanovic et al., 2017). Since the direct connection between career discussion and ASE is not shown (see upcoming section). This highlights there a dire need to evaluate the current scenario to reframe career-discussion opportunities so that grade-12 level population could be able to get advantage from career-related discussions at school.
Parallel with educational institutions family’s contribution in growth of ASE is realized in the presence of mediators: career interest and independence learning ability. Findings suggest that students’ family involvement is potential to raise career interest and independent learning abilities which in turn affect ASE. The results are in line with prior study by K. Iqbal and Modood (2023). This is because in extended family structures similar to those in Pakistan, students are able to seek help and discuss academic viewpoints with siblings/ cousins and even older successful ones (Ahmed et al., 2022). Role is siblings/cousins are important to think when parents lack ability to support at secondary and upper secondary levels of education (Ma et al., 2002; Parveen et al., 2022).
Furthermore, it is worthy to think that in the recent technological era, technology does not show direct but indirect influence on ASE on sample students. The problem-solving emerges a key mediator. This implies that students’ ASE beliefs are shaped when they receive technological support to overcome challenges, such as understanding difficult concepts, clarifying course material, and addressing misconceptions (Fitton, 2013; Hwang et al., 2018; Magis-Weinberg & Berger, 2020). The findings support the literature for the potentiality of technology in providing ample support for students (Rodriguez-Segura, 2022; Siddiqui et al., 2020a).
However, in contrast with some studies (Abdullah & Rahman, 2020), our study found that decision making does not greatly influence on pupils’ learning behaviors. The reason may be due to perceived age and cultural factors, where teenagers are not explicitly involved in autonomous decision making since they largely rely on parents/highly educated others to choose for them (Altaf et al., 2021). Despite the low level of decision-making engagement, the students were confident and motivated despite self-high expectations and a clear career interest. Perhaps further qualitative inquiry could provide detailed insights into the role of decision making in ASE.
Educational Experiences and Achievement
The study indicates that students did not see higher grades as resulting in higher self-efficacy. The findings are inconsistent with prior literature (Smith & Hirschl, 2022; Van Dinther et al., 2011). Perhaps, the grades mainly represent students’ ability to reproduce facts and knowledge while neglecting the focus on attitude toward learning (as also discussed in Hinduja, 2021; Ilyas & Azam, 2022). In the context of a developing nation like Pakistan, quantitative gains/grades in examination do not appear to show connection with qualitative gains (i.e., students’ level of motivation and self-regulation; Ilyas & Azam, 2022). However, peer-learning is seen as factor triggering self-efficacy. Peers are influential persons whom students discuss their concerns, get feedback on their academic assignments and seek help about how to deal with academic life complexities. Such discussions may trigger their self-regulatory mechanism, similar outcome are evident in literature (Bećirović et al., 2022; Blaskova & McLellan, 2018; Guay et al., 2022; Hwang et al., 2018; Kristianto & Gandajaya, 2023; Schunk & DiBenedetto, 2021).
Likewise, safety has been shown as one of the strongest predictors of ASE, this is school environment free of harassment, fear and insecurity can promote academic self-efficacy. This is may be due to in a safe environment students feel welcome to share their opinions and able to learn new perspectives from diverse others (Edmondson et al., 2016; Flensner & Von der Lippe, 2019), however unsafe environment may resist students’ willingness to take part in discussions (Cornell, 2021; Edwards et al., 2021). Since, much literature pertaining to safety linked to western population, our findings contribute in south-Asian context.
The study founds lack of direct connection between class participation, teacher feedback and ASE. This shows that students did not see teachers and schools role in developing their self-efficacy. This is because the primary role of the teacher in this context consists of delivering content rather than nurturing a student’s thinking and learning attitude (Ilyas & Azam, 2022). Teachers’ feedback perhaps lacks utility in raising individuals’ learning and thus fails to contribute to their self-efficacy (Fatima et al., 2022; Hattie & Timperley, 2007; Wisniewski et al., 2020), while, educational experiences in classrooms that is, classroom participation, teacher feedback and career discussion had an indirect effect on their self-efficacy. This suggests that students will grow in confidence, become problem solvers, and independent learners if they are provided with the chance to ask questions and share concerns, receive timely and relevant feedback. The analysis shows that meaningful learning experiences are essential in providing students with an enabling environment to nurture their confidence and motivation.
Further, some factors associated with educational institutions, such as high expectations from teachers, were insignificantly influenced by the results. In other words, teachers’ methodology, such as task design and reinforcement, does not affect ASE equally for all students. This may be due to teachers’ expectations lack concrete and meaningful learning experiences as suggested (Demie, 2022; Johnston et al., 2021) or may be teachers’ expectations are biased and low for some or a group of students (Demie, 2022). Another reason may be due to an intermediate level of education in Pakistan, teachers’ methodology is largely examination-oriented, classroom tasks are often repeated and too superficial to encourage innovation and look at the learning course with creative perspectives (Rind & Mari, 2019).
Consistent with studies (Ilyas & Azam, 2022; Zahoor & Mahmood, 2023), the role of schools and teachers regarding career discussion did not have a direct significant impact on students’ self-efficacy; this suggests that the importance of career discussion is not perceived. The findings are inconsistent with prior studies (Santilli et al., 2020; Stipanovic et al., 2017). The reason for this may be that many schools lack career counseling insights and the ability to have quality career discussions with students (Ilyas & Azam, 2022; Zahoor & Mahmood, 2023), rather than allowing students to choose their career, the school imposes its choices on them (Ilyas & Azam, 2022; Hinduja et al., 2023).
Moreover, the analyses found an insignificant relationship of extra-curricular activities with ASE. This shows that ECA is perceived differently for sample students. Some students may perceive ECA’s significance while others do not. The results are consistent with the conclusion by Javaid et al. (2020), that students may not comprehend the connection of ECA with their academic achievement; they feel less motivation to participate. Nevertheless, the findings are inconsistent with the western context (Buckley & Lee, 2021; Griffiths et al., 2021, p. 1297). Contrary to our findings, ECA has shown a positive effect on academic performance in past studies (Muhammad et al. 2022; Rahman et al., 2021; Rathore et al., 2018). In addition, future qualitative studies may investigate how ECA are conceptualized, how they are organized, and how teachers and families respond to student participation.
Out of School Experiences
We analyzed out-of-school experiences, including hobbies, technology use, and students’ participation in community activities, regarding self-efficacy. This study indicates that educated community members and coaches play influential roles within the sample population. Students’ participation in community activities has an impact on their achievement and learning efficacy, as noted by Valentine et al. (2002). This could be attributed to community members, including peers and elders, providing insights into various domains and related career opportunities, which in turn may influence self-regulating behavior (Bandura, 1997; Charleston & Leon, 2016).
Similarly, students’ hobbies also affect their self-efficacy in the academic realm, as observed by Griffiths et al. (2021) and Valentine et al. (2002). The results suggest a positive connection between students’ involvement in academic/personal development pursuits (reading/ technical skills/ emerging technology) and their ASE. The reason may be a student’s belief that their hobby is meaningful for their mental, intellectual, and emotional development (Balan et al., 2019). The results are similar to prior studies (Balan et al., 2019; Valentine et al., 2002).
Also, engagement in baking as a hobby has a significant impact on their ASE. Various reasons could account for students’ engagement in baking. These reasons include the influence of social media, increased interest in culinary endeavors, and the appreciation and recognition received from family and friends. However, other hobbies such as sports/indoor games, artistic/creative activities (gardening, traveling, painting, handicrafts, dancing), and academic/personal development pursuits (reading, technical skills, emerging technology) do not significantly impact academic situations in Pakistani higher secondary education. These findings align with the previous study conducted by Javaid et al. (2020).
Furthermore, technology has demonstrated an indirect influence on ASE, as suggested by Rodriguez-Segura (2022) and Yan (2018). However, this connection is significant only when problem-solving behavior serves as a mediator.
Furthermore, technology has demonstrated insignificant direct impact. This highlights that not all students are equally benefitted by technology. The results support Dienlin and Johannes (2022) arguments that focus and plans define the uselessness of technology for students. Also, students’ characteristics such as thought patterns and society network (Odgers & Jensen, 2022) and sensitivity to technology could matter (Zaheer, 2018). Thus the findings caution against inactive and unplanned technology engagement, as it will not impact ASE. On the other hand, the indirect influence is supported (see in behaviour and values).
Conclusion
Based on our analysis, ASE can be perceived as a dynamic and multidimensional phenomenon that flourishes within a supportive environment. Theoretically, we identified four distinct categories of variables that foster students’ self-efficacy. However, this research discovered that students’ behaviors, values and experiences outside of school are the primary contributors. Formal educational experiences and family background, on the other hand, did not directly influence students’ self-efficacy, except for the aspect of peer learning, which was seen as a secure mode of learning within the same age group. These findings suggest that traditional teaching methods, limited educational goals, and inadequate parental understanding of their role in nurturing confidence are not integral components of our current formal education system. Therefore, the study proposes that to consider self-efficacy as an educational outcome, we need to reassess the purpose of schools, the responsibilities of teachers, our understanding of learners and the learning process, as well as parental education regarding their role in fostering students’ self-efficacy. Additionally, we recommend conducting qualitative research to gain insights into the direct and mediating effects of the four selected categories of variables. Furthermore, teacher education programs must include courses that focus on nurturing self-efficacy and its implications for developing positive learning habits and outcomes.
Implications
The study’s results have both theoretical and practical implications. The self-efficacy theory of Bandura is supported by the outcomes of this study. Additionally, there is practical implications for teachers, educational institutions, family such as parents, siblings/cousins and career counselors.
Theoretical Contribution
Bandura, Socio-cognitive theory predicts the sources of self-efficacy. The theory states that mastery experiences, verbal persuasion, vicarious experiences, and affective states can enhance self-efficacy. The study shows that motivation by peers (as verbal persuasion) and role model peers/community members (vicarious experiences) contribute to ASE of students. Similarly, problem-solving skills and independent-learning (i.e., mastery experience) can equally promote self-efficacy. Additionally, career interest and psychological safety (as affective states) help the development of ASE.
In addition, Deci and Ryan’s (1985) Self-determination theory is bolstered, the theory highlights the role of social factors, that is, the events that support learners’ autonomy, and competence and relatedness foster motivation. Our results highlight that independent learning (autonomy) enhances self-efficacy (motivational beliefs) and independent learning can be fostered by class-room design and activities and family involvement (social factors). Similarly peer/community members (relatedness) influence self-efficacy (motivation).
Practical Contribution
The findings have practical contributions for teachers. It is important for teachers to recognize that to grow academic self-efficacious students must need to develop behaviours and values that is, career interest, problem-solving skills and independent learning abilities, and classroom design and teacher feedback has potential for such development. Thus the findings provide cues for reflecting on teachers’ pedagogy. Since findings show the significant role of peer-learning in the development of ASE, this suggests the role of educational institutions in creating spaces for peer collaborations. The results demonstrate the role of family education and nurture in the development of learning behaviors and values, i.e., siblings, cousins, aunts, and communities. The findings also show that career discussions lead to ASE through career interest, which is vital for teachers or career counselors when they interact with students in related discussions with students.
Limitations and Future Research
The study has a methodological limitation as it is confined to a quantitative self-report questionnaire. Self-report data can be subject to response bias, as actual results may differ than those of students have reported (Rotgans & Schmidt, 2012). Although self-reports are the least reliable tools to measure (Rovai et al., 2014), due to lack of procedures in determining truthfulness in students’ responses, the student marked responses were assumed valid and considered reliable (Warner, 2013). Qualitative design could provide insights into students’ experiences, both positive and negative, regarding the impacts of various factors such as background, education, and non-educational influences, facilitate understanding of experiences across different fields of study, such as Science, Commerce, and Arts & Humanities, and explore the relationship between students’ experiences and Academic Self-Efficacy (ASE).
Furthermore, the study employed convenience sampling, since the data was collected from an accessible population, thus generalizability is limited (Gall et al., 2007). The study assumed to recruit participants representative of all intermediate students in metropolis, Pakistan. However, it could not meet the assumption to obtain accurate representation of the entire population, further studies need to be conducted. A replicated study with random sampling could yield more robust results. Additionally, since this study focused on intermediate/higher secondary level students, future researchers can adapt this instrument to investigate diverse pools and populations of students, including those at the secondary and tertiary levels, to explore similarities, differences, and outcomes.
This study has observed the direct linkage of health and ASE, the result was insignificant. Future researchers can identify the linkage of absenteeism caused by sickness with students ASE, this will help explore the influence of health.
Footnotes
Acknowledgements
The Article Processing Charges (APC) are covered by Technische Universität Berlin through the Project DEAL agreement.
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) received no financial support for the research, authorship, and/or publication of this article.
Ethical Approval
The researchers followed basic ethical principles and the APA’s ethical code. Participants provided informed consent after reading details about the purpose of the study, anonymity, free participation, planned use of data, and the right to end participation without negative consequences. In this way, informed consent was assured according to the ethical guidelines and federal legislation. Ethical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements. The entire study and questionnaire were reviewed by the second author’s research team from a private university in the Metropolis City of Pakistan who are well acquainted with the educational system of Pakistan. The team of reviewers found no potential conflict of interest or harm to participants, nor any activities that went beyond the ethical code of conduct.
Data Availability Statement
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.