The mediating role of goal orientation in the relationship between formative assessment with academic engagement and procrastination in medical students

Abstract

Background

Academic involvement and academic procrastination are two behavioral variables and are among the challenges of higher education, especially medical education. The purpose of the current research is to investigate the mediating role of goal orientation in the relationship between formative assessment with academic engagement and procrastination in Iranian medical students.

Methods

The present correlational study of path way type, was performed on 388 students of Zanjan University of Medical Sciences in the 2021 selected by a convenient sampling method. Four questionnaires of Goal orientation scale )21-item), the classroom assessment approaches questionnaire (12-item), the Procrastination Assessment Scale– Students (44-item) and the student engagement scale (10-item) were used to collect data. The data were analyzed with SPSS-26 and LISREL-10.2 software.

Results

The results of the path analysis showed formative assessment have significant direct effect on mastery orientation (β = 0.40), performance-approach (β = 0.14), avoidance orientation (β = -0.28), academic engagement (β = 0.32) and academic procrastination (β = 0.12). Also mastery orientation (β = 0.13), performance-approach (β = 0.12), avoidance orientation (β = -0.25) have a significant direct effect in the variance of academic engagement. As well mastery orientation (β = -0.43), performance-approach (β = -0.15), avoidance orientation (β = 0.30) have a significant direct effect in the variance of academic procrastination. These results confirm the direct hypotheses. Indirect effect of formative assessment to academic engagement (0.21) and academic procrastination (0.27) was significant.

Conclusion

It is recommended according to the results practitioners provide the basis for promoting academic engagement and decrease academic procrastination through the application of formative assessment and Improve classroom goal orientation.

Introduction

Medical education is crucial for the advancement of healthcare systems globally [1, 2]. Its main goal is to prepare medical professionals to deliver top-quality services throughout their careers [3]. Academic learning equips students with essential knowledge and skills [4]. However, medical students face heavy academic burdens, managing rigorous schedules, teaching content, and tasks, leading to high pressure [5, 6]. On the other hand, rapid changes in teaching and evaluation methods worldwide underscore the need for continuous improvement [7]. Assessment and evaluation aim to enhance student learning, and the content and methodology of evaluation significantly influence the quality of that learning [8]. While Iran’s medical education system has made significant progress over the last three decades, it is crucial to emphasize the importance of social accountability within the health system and at the level of medical schools. To ensure a competent healthcare workforce, accountability for the quality of services provided and the knowledge, attitude, skills, and abilities of graduates is essential [9].

Classroom assessment is a crucial tool for enhancing the learning process [10] often referred to as “assessment for learning” rather than “assessment of learning” [11]. Formative assessment, in particular, has been linked to academic engagement [12, 13] and procrastination [14]. According to the Assessment Reform Group, formative assessment is a process where both learners and teachers seek and interpret evidence to determine the learners’ current progress, future goals, and the best path to achieve those goals [15]. Moss and Brookhart define formative assessment as a feedback-driven process during instruction, aiming to improve learning and teaching activities and ultimately increase student achievement [16]. Wafubwa’s meta-analysis revealed that formative assessment not only improves grades but also enhances academic motivation and engagement among learners [17]. By providing students with feedback and insights into their understanding of the material [18, 19], formative assessment serves as a predictor of outcomes [20, 21] and guides their efforts toward self-regulated learning [22]. Academic engagement and procrastination are significant variables influencing how programs and academic tasks are executed, particularly for medical students [23].

Academic procrastination, a subtype of situational procrastination [24], refers to the deliberate delay in initiating or completing tasks related to the learning process [25]. In medical education, procrastination is a prevalent issue that hinders students’ academic progress [26]. While many studies have examined academic procrastination in various educational contexts, most research has focused on the university setting [24, 27]. Notably, students who struggle with procrastination often express a desire to overcome this habit [27].

Student engagement has gained prominence due to the increasing pressure on students to complete their studies within specified timeframes [28, 29]. High levels of engagement are crucial for academic performance and persistence in educational tasks and institutions [30, 31]. Academic engagement is typically characterized as a multidimensional construct, although its definitions vary across literature. The emotional, cognitive, and behavioral aspects of student engagement have been the most studied and are considered essential factors in understanding student involvement and success [28, 30].

Goal orientation, a motivational variable, has been frequently studied in relation to procrastination [32] and academic engagement [33]. The goal orientation theory of achievement motivation is a social cognitive theory applied in educational contexts to explain student behavior [34, 35]. It suggests that variations in behavior are not solely due to differences in motivation levels. Goal orientation refers to the reasons or purposes behind students’ learning, and these goals influence their actions, reactions, and motivation to learn [34, 36].

Research on academic procrastination highlights the need for systematic investigations into the negative impact of procrastination on students’ academic goal achievement and the exploration of strategies to mitigate procrastination [24]. Conversely, goal orientation can enhance achievement, particularly under challenging conditions [37]. Achievement goal behaviors have been found to independently predict academic achievement and are influenced by mediating or moderating relationships with other student behaviors [38, 39].

One of the theories that can be considered to explain the theoretical framework of this research is the achievement goal theory [40] which Cook and Artino [41] emphasized on the need to pay attention to in medical education. According to this theory, students have goals for their learning and bring them to class. These goals, which are classified as mastery, performance and avoidance, affect how to learn and academic results. But educators can also influence the learning goals of students by modifying the educational environment [42]. Teaching and assessment are two important tools of the instructor in setting up the educational environment. In new approaches, assessment is considered as a part of education and is a tool to improve teaching and learning. Therefore, the use of new assessment approaches, which are called formative assessment, enriches the educational environment and moves the learners’ goals from performance and avoidance to mastery. According to the achievement goal theory, each of the goal setting activates related behaviors. Two important learning behaviors in medical education are academic engagement and procrastination. It is expected that students who pursue performance and avoidance goals have more procrastination and less engagement in the learning process. On the other hand, the group that has mastery goals engages enthusiastically with the learning content during learning and therefore has more active participation. Although theories and limited studies [43, 44] confirm the relationship between goal orientation and academic procrastination, but the mediating role of goal orientation has not yet been determined, considering this research gap, the present study was conducted with the aim of investigation the mediating role of goal orientation in the relationship between formative assessment with academic engagement and procrastination in Iranain medical students. The hypotheses of this study were as follows: 1- formative assessment is related to academic engagement through goal orientation, 2- formative assessment is related to academic procrastination through goal orientation, 3- The assumed model has a good fit.

Methods

Design and data collection

A correlational path analysis study was conducted on students of Zanjan University of Medical Sciences in 2022. According to Kline [45], the sample size for path analysis should ideally be 10–20 times the number of parameters. Questionnaires were distributed to 400 students, with professional interviewers encouraging participation and explaining the research objectives. Incentives, such as gift pens, were also provided. Out of the 400 questionnaires distributed, 12 were excluded due to incomplete or outlier data, resulting in a final sample size of 388, which exceeds Kline’s recommended minimum. The response rate for the study was impressive at 97%. The sampling method employed was convenience sampling.

The participants were given the option to choose between a paper or online version of the questionnaire. The first page of the questionnaire explained the purpose of the research, the criteria for participation, and included a consent form. After providing consent, participants answered demographic questions on the second page, and then proceeded to complete four additional questionnaires: the Classroom Assessment Approaches Questionnaire (CAAQ), the Procrastination Assessment Scale for Students (PASS), the Goal Orientation Scale, and the Student Engagement Scale.

Instruments

The Classroom Assessment Approaches Questionnaire (CAAQ) was employed to assess students’ perceptions of their teacher’s classroom assessment methods. This 12-item questionnaire, which includes questions such as “Did you receive any feedback on how you learned while studying?,” was designed by Yousefi Afrashteh et al. [46] specifically for use in Iran. A high score on the CAAQ indicates that the teacher utilizes formative assessment practices more frequently. The reliability coefficient of the questionnaire, as reported by Yousefi Afrashteh et al. [46]. was 0.72. In a separate study on Iranian medical students [47]. the Cronbach’s alpha coefficient for the CAAQ was found to be 0.78, indicating good internal consistency. In the present study, the Cronbach’s alpha coefficient for the CAAQ was also calculated to be 0.78, further supporting its reliability.

The Procrastination Assessment Scale– Students (PASS) (Solomon & Rothblum, 1984) was used to measure academic procrastination [48]. This 44-item questionnaire includes two subscales: Areas of Procrastination (AOP; 18 items) and Reasons for Procrastination (26 items). Respondents are queried about their procrastination frequency, their perception of procrastination as a problem, and their desire to reduce it. The present study utilized only the six AOP subscale items related to the degree of procrastination. Responses are rated on a Likert scale ranging from 1 (“never procrastinate/not at all a problem/do not want to decrease”) to 5 (“always procrastinate/always a problem/definitely want to decrease”). Jokar and Delavarpour confirmed the factorial structure of this questionnaire for the Iranian sample using factor analysis [49]. In the current study, the Cronbach’s alpha coefficient for internal consistency was 0.80, indicating good reliability.

Goal orientation scale (Bouffard et al. 1995) and the scale designed by Armes and Archer (1998) was employed to assess individuals’ goal preferences in academic contexts [50]. This scale evaluates three dimensions: learning goal orientation, performance goal orientation, and failure avoidance goal orientation. Respondents indicate their level of agreement with 21 statements on a 6-point Likert scale ranging from “absolutely disagree” to “absolutely agree.” The scale includes 8 items related to learning, 4 to performance, and 9 to failure avoidance. Khademi and Noshadi (2006) confirmed the validity of this questionnaire using internal consistency measures [51]. The reliability coefficients obtained were 0.83 for learning, 0.72 for performance, and 0.85 for failure avoidance. To assess reliability for the present study, the questionnaire was administered to 50 students, yielding Cronbach’s alpha values of 0.84 for learning, 0.78 for performance, and 0.83 for failure avoidance. The overall Cronbach’s alpha for this questionnaire in the current study was 0.76, indicating acceptable reliability.

The student engagement scale. To assess student engagement, we utilized the student engagement scale developed by Gunuc and Kuzu (2014), which has been previously employed to explore the impact of classroom technology on student engagement [52]. This scale evaluates six types of engagement, categorized under class engagement and campus engagement. The four class engagement scales, namely cognitive engagement, peer relationships, relationships with faculty members, and behavioral engagement, were tailored to refer to specific courses using a frame of reference (e.g., “I feel myself as a part/member of a student group for [COURSECODE]”),” see “Procedure and design” section for further details). The cognitive engagement scale comprised 10 items, such as “I motivate myself to learn for [COURSECODE],” and demonstrated good internal consistency (α = .89 for the official Facebook course and α = .86 for the non-official Facebook course). (see “Procedure and design” section for further details). The peer relationships scale included six items (e.g., " internal consistency (α = .87 for both official and non-official Facebook courses). The relationships with faculty members scale consisted of 10 items, such as “My teachers in [COURSECODE] show regard to my interests and needs,” and demonstrated good internal consistency (α = .89 for the official Facebook course and α = .92 for the non-official Facebook course). The behavioral engagement scale, consisting of four items (e.g., “I follow the rules in class for [COURSECODE]”), exhibited acceptable internal consistency, with Cronbach’s alpha coefficients of α = .75 for the official Facebook course and α = .66 for the non-official Facebook course. Moving beyond class engagement, the scale also included two campus engagement scales: valuing and sense of belonging. These scales were presented without a specific course frame of reference. The valuing subscale, comprising three items (e.g., “I believe university is beneficial for me”), demonstrated good internal consistency (α = .79). Meanwhile, the sense of belonging subscale, with eight items (e.g., “I feel myself as a part of the campus”), also showed good internal consistency (α = .88). All engagement scales were rated on a 5-point scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), and item responses were averaged to create composite scales. In the present study, the overall Cronbach’s alpha coefficient for this engagement scale was 0.82, indicating good reliability.

Statistical analysis

Descriptive and inferential statistics were utilized in the analysis of the data. In the descriptive analysis, the frequency distribution table of demographic variables, as well as the mean and standard deviation of variables, were examined and reported. Inferential statistics, on the other hand, involved the use of Pearson’s correlation coefficient and path analysis. The latter was performed using LISREL v10.2, while SPSS v.26 (IBM) was employed for the remaining analysis. Prior to conducting the path analysis, its fundamental assumptions were verified, including the requirement of a minimum sample size of 200 participants, as recommended by Kline [45]. The sample of 322 people supported the assumption. The normality of the distribution of the dependent variables, as shown in Table 1, fell within the range of -1 to 1 on the skewness index, confirming normality. The analyzed model revealed no correlation between the errors of the endogenous variables, satisfying another assumption. Furthermore, all variables were measured on an interval scale. In addition to direct effects, this study considers several indirect effects, specifically the impact of formative assessment on academic engagement and procrastination through goal orientation. Goodness of fit indices was used to evaluate the overall model fitness and determine how well the conceptual model aligns with the data. This study utilized several indices, including the likelihood ratio chi-square (χ2), the ratio of χ2 to degrees of freedom (χ2/df), the goodness of fit index (GFI), the adjusted goodness of fit (AGFI), the root mean square error of approximation (RMSEA), and the comparative fit index (CFI). These indices provide a comprehensive assessment of the model’s fitness and the strength of the relationships between the variables.

Table 1 Descriptive statistics for research variables and correlation coefficient between them

Results

Table 2 reports the demographic information of the participants. Out of 388 students participating in this study, 20% of the participants were in the age group of less than 20 years and 47% in the age group of 20–25 years. 26% of the participants were married. 71% of the participants were undergraduate students, 21% were postgraduate students and 8% were PhD students. 51% of them were employed while studying. 32% of the participants studied in the School of Public Health, 37% in the School of Allied Medical Sciences and 31% in the School of Nursing and Midwifery. More details are showed in Table 2.

Table 2 Demographic statistics of the participants

Table 1 shows mean and standard deviation for research variables. In addition, Pearson correlation is reported to determine the relationship of all variables included in the path model. The mean and standard deviation of Academic well-being are 40.40 and 8.27, respectively. The correlation coefficient of academic well-being with formative assessment was 0.02, with self-efficacy was 0.39, with internal value was 0.28, with test anxiety was 0.26, with cognitive strategies was 0.19 and with self-regulation was 0.28. Apart from the relationship between academic well-being and formative assessment, other correlation coefficients are significant at the level of 0.001.

The results of path analysis to investigate direct, indirect and total relationships are reported in Table 3.

Table 3 Path coefficients for direct, indirect and total relationships

Table 3 shows the direct, indirect, and total effects for the relationship of the variables in the model. According to the results of this table, formative assessment has significant direct effect on mastery orientation (β = 0.28, P < 0.001), avoidance orientation (β = -0.26, P < 0.001), academic engagement (β = 0.12, P < 0.016) and academic procrastination (β = -0.29, P < 0.001). Also, mastery orientation (β = 0.35, P < 0.001), performance-approach (β = -0.11, P < 0.013), avoidance orientation (β = -0.12, P < 0.020) have a significant direct effect in the variance of academic engagement. As well mastery orientation (β = -0.13, P < 0.006) and avoidance orientation (β = 0.03, P < 0.569) have a significant direct effect in the variance of academic procrastination. These results confirm the direct hypotheses. According to the results of Table 4, indirect effect of formative assessment to academic engagement (0.12, P < 0.001) and academic procrastination (-0.09, P < 0.001) is significant. These results confirm that goal orientation plays a mediating role in the relationship between formative assessment with academic engagement and academic procrastination. In fact, part of the relationship between formative assessment with academic engagement and academic procrastination occurs through changes in coping self-efficacy.

Table 4 The goodness of fit indices for the models

Standard estimate (and t-value) for relationship between variables has showed in Fig. 1.

Fig. 1

Standard estimate (and t-value) for relationship between variables

The goodness-of-fit indices reported in Table 4 shows that the analyzed model has an acceptable fit (P-value = 0.60; chi square = 0.99; df = 2; chi square/df = 0.49; RMSEA = 0.001; CFI = 0.99; AGFI = 0.99).

Goodness-fit indices are reported in Table 4.

Conclusion

This research investigates how formative assessment affects students’ academic engagement and procrastination, examining the role of goal orientation as a key intermediary. The findings, based on Structural Equation Modeling (SEM) analysis, show that the proposed model accurately represents the relationships between these variables, highlighting a significant connection between formative assessment, goal orientation, and both procrastination and engagement. Importantly, the analysis revealed that age and gender did not have a moderating effect on these relationships, thereby confirming the study’s initial hypotheses regarding the impact of formative assessment on student behavior.

The study’s first hypothesis, which proposed a link between formative assessment and academic procrastination via goal orientation, was supported by the findings. In essence, the results suggest that formative assessment influences procrastination indirectly through its impact on goal orientation. While this specific pathway has not been previously explored, the current study’s results align with and build upon existing research that has investigated the individual relationships within this pathway, providing new insights into the complex dynamics between formative assessment, goal orientation, and procrastination [53, 54]. According to Elliot and McGregor’s model (2001), which informs the interpretation of the current results, there are four distinct types of goal orientation: mastery-oriented, mastery-avoidance, performance-oriented, and performance-avoidance goals [55]. Each of the four goal orientations (mastery-oriented, mastery-avoidance, performance-oriented, and performance-avoidance) is characterized by distinct cognitive, behavioral, and emotional patterns. Research suggests that mastery and performance goals are negatively correlated with procrastination, as they promote effective self-regulation. In contrast, performance-avoidance goals are positively linked to procrastination, as they involve self-regulatory processes that are incompatible with task engagement and instead foster avoidance behaviors [49]. According to Midgley and Urdan (2001), the structure of an individual’s goals serves as a potent cognitive framework that can significantly influence both their goal-setting and overall performance [56]. In contrast, studies emphasize that formative assessment should focus not only on the ultimate goals, but also on the methods and instruments used to achieve them. By doing so, formative assessment becomes a vital tool for continuously improving and adapting educational programs and activities, ultimately ensuring they meet their desired outcomes [34]. Due to its dynamism and breadth [7], formative assessment can be leveraged to explore the relationship between goal orientation and academic procrastination, offering a nuanced understanding of how these factors intersect and influence one another.

The study’s second hypothesis, which posited that formative assessment is linked to academic engagement via goal orientation, was supported by the findings. This suggests that formative assessment can indeed influence academic engagement indirectly through its impact on goal orientation. While no prior research has directly examined this specific pathway, the current study’s results are consistent with existing literature on the individual relationships that comprise this path [57, 58].

Research by Koh, Lim, and Habib (2010) found that formative assessment in Singapore has a positive impact on both teacher and student learning outcomes, largely due to the integration of professional development strategies into instructional planning [59]. Through formative assessment, teachers employ a range of assessment activities and strategies in the classroom to gain a comprehensive understanding of student learning. This information is then used to inform instruction, provide constructive feedback, and adjust teaching approaches. Students play an active role in this process, not only participating in learning activities but also using assessment data to set personal goals, make informed decisions about their learning, and develop a sense of self-efficacy in their academic pursuits.

Wuest and Fisette (2012) suggest that formative assessments serve as a valuable tool for teachers, providing insight into student learning and informing instructional planning for future lessons, thereby enabling teachers to adjust their teaching strategies and better meet the needs of their students [60]. According to Ritchhart, Church, and Morrison (2011), this educational approach empowers students to take ownership of their learning from the outset, entrusting them with responsibility for their own educational journey and fostering a sense of agency and autonomy in the learning process [61]. This approach enables students to actively construct their own understanding of the subject matter, work collaboratively with their peers, and progress towards more sophisticated knowledge and insights. As noted by Moss and Brookhart (2009), one key benefit of sharing learning objectives with students is that it allows them to engage in tasks that are explicitly aligned with those objectives, promoting a clear sense of direction and purpose in their learning [62].

According to Heritage (2008), when students are aware of the learning goals and criteria, they can transform from passive recipients of information to active participants in the learning process, taking a more engaged and invested role in their own education [63]. When introducing a new subject, it is crucial to clearly communicate the learning objectives, requirements, and criteria to students, ensuring they have a shared understanding of what is expected and what they will be working towards [64, 65].

In this educational approach, students are entrusted with autonomy over their own learning from the outset, as Ritchhart, Church, and Morrison (2011) suggest, empowering them to take ownership of their educational journey and make informed decisions about their own learning process [61]. By adopting this approach, students are able to take an active role in building their own understanding of the subject matter, working together with their peers, and progressing towards deeper and more nuanced knowledge. As Moss and Brookhart (2009) point out, sharing clear learning objectives with students has the added benefit of enabling them to engage in targeted tasks that directly align with those objectives, thereby promoting focused and effective learning [62]. The evidence suggests that formative assessments, when integrated with goal-oriented approaches, can have a profound impact on student learning, fostering increased academic engagement and transforming the learning process into a more vibrant and interactive experience.

Application of study results

Given the potential of formative assessment through goal orientation to address procrastination and enhance academic engagement, the findings of this study offer a valuable resource for policymakers and education officials at both local and national levels, providing a potential solution to improve the country’s education system and promote more effective learning outcomes. The aforementioned study offers a beacon of hope in this landscape, furnishing actionable insights that can catalyze tangible change. By identifying the nexus between reducing work procrastination and augmenting academic participation, the research underscores the pivotal role of proactive and disciplined work habits in driving student engagement. Through a comprehensive analysis of the study findings, educators and administrators in the medical education domain can glean invaluable strategies to curtail procrastination and invigorate student involvement. In addition to these insights, the study advocates for the integration of collaborative and interactive learning methodologies to enhance academic participation. By fostering an inclusive and participatory learning environment, educators can engender a sense of camaraderie and shared accountability among students, dissuading them from withdrawing into the quagmire of procrastination. Encouraging peer-to-peer interaction, group discussions, and collaborative projects can infuse the academic milieu with dynamism, propelling students to actively partake in the educational discourse.

The limitations of the study

One of the limitations of this study is related to the cross-sectional nature of the study. These studies provide information in a specific period of time and have less predictive power compared to longitudinal studies. Also, although structural equation modelling has been used in this study, the nature of the relationships obtained is relational and not causal, and due to the statistical method used and the cross-sectional nature of this study, causal perceptions This type of study is not suitable. In addition, this study was used on a sample of Iranians, and due to the existence of differences in educational systems, extreme caution should be exercised in generalizing these findings to other societies.