Is Service Learning Factor That Influences College Selection

1. Introduction

Knowledge transfer, the power to use cognition and skills learned in school into a new situation, is an important indicator of educational success (Bransford and Schwartz, 1999; Wang et al., 2020), particularly for college students, as most of them will enter the workforce afterward graduation and will exist expected from their employers to utilise what they have learned in higher into accurate situations. Promoting students' deep learning and knowledge transferability is specially critical for the Chinese education system, as information technology has been criticized for emphasizing too much on helping students accomplish good exam scores in standardized tests (Guo-Brennan, 2016) and impeding students' abilities to transfer what they accept learned in class to real-life situations (Guo et al., 2016a). Service learning (SL), a pedagogical method that combines academic learning and customs service, may accept great potential for promoting students' noesis transfer because it offers students opportunities to utilize what they accept learned in classrooms to serve communities in existent-life contexts (Wang et al., 2019b). Information technology has been advocated for decades in Western countries (Furco et al., 2016) and considered one of the loftier-impact educational practices in college education (Kuh, 2008); however, to promote SL in gimmicky Chinese educational activity, more than empirical evidence that supports the impact of SL on Chinese students' outcomes is needed.

Mounting evidence suggests that SL benefits college students' academically, professionally, and personally (Eyler and Giles, 1999; Knapp et al., 2010; Yorio and Ye, 2012; Bringle et al., 2016; Furco et al., 2016). Nevertheless, mixed findings have also been reported regarding the bookish benefits of SL for students (Furco et al., 2016; Song et al., 2017). Recently, more attention has been directed toward the dynamic processes and mechanisms of students' development during SL (Li et al., 2016; Guo et al., 2016b), as these variables are critical to better understand how SL works, when SL is effective, and who SL benefits, especially as SL experiences are increasing in number beyond institutions of higher teaching (Furco et al., 2016). Using a case study arroyo, Guo et al. (2016b) found that higher students' behavioral, emotional, and cognitive engagement fluctuated over the 9-week SL program. Based on the characteristics of students' appointment evolution, they divided the whole SL into four developmental stages: confusion and hesitancy, enlightenment and enthusiasm, fluctuation and aligning, and stabilization and routinization.

While a growing body of research has shown the positive impact of SL on higher students' knowledge transfer (Markus et al., 1993; Eyler and Giles, 1999; Deeley, 2010; Prentice and Robinson, 2010; Gerholz et al., 2018; Wang et al., 2019b), data about the dynamic processes of noesis transfer development during SL have not yet been documented. This written report therefore gear up out to investigate the evolution characteristics of higher students' knowledge transfer within the context of a ix-week SL plan. Nosotros designed a longitudinal study to runway students in SL past measuring their noesis transfer at 8 time points. Previous research suggests that higher students' cocky-reports of noesis transfer tin can provide valuable information about their knowledge transferability (Wang et al., 2020). Several studies have shown that college students' perceived knowledge transfer is positively associated with their perceived learning and course grades (Hsu et al., 2019; Wang et al., 2019a). Considering assessing actual transfer operation at multiple times costs researchers' laborious hours, in the current research, nosotros studied college students' perceived knowledge transfer instead of their actual cognition transfer.

In addition to examining the dynamic process of college students' knowledge transfer during SL, factors that influence the evolution characteristics of noesis transfer are also important. While there are a number of perspectives to view student knowledge transfer development, the current study focuses on mastery goal orientation and perception of psychological control, as these two factors are well-grounded in the literature of education as consistent predictors of educational success (Kaplan and Maehr, 2007; Senko et al., 2011; Soenens et al., 2012; Ryan and Deci, 2017). Students with mastery goals orientation focus on acquiring and developing competence (Senko et al., 2011). Previous research has shown that students with mastery goal orientation performed better on a transfer task than the ones with performance goals (Bereby-Meyer and Kaplan, 2005; Belenky and Nokes-Malach, 2012). For example, Belenky and Nokes-Malach (2012) studied 104 undergraduates to investigate how students' achievement goals interact with dissimilar forms of instruction to heighten transfer. They found a positive impact of mastery goal orientation on transfer. Students with mastery goal orientation are more likely to adopt deep learning strategies to process the learning materials, which may promote their knowledge transferability. The 2nd gene, perception of psychological control, is grounded in self-determination theory (Deci and Ryan, 1985; Ryan and Deci, 2017). In the current study, perception of psychological control refers to the extent to which students perceive intrusive behaviors that pressure them to act, recollect, and feel in particular means from their SL supervisors (Soenens et al., 2012). A correlational written report conducted by Soenens et al. (2012) has shown that higher perceptions of psychological command were associated with lower metacognitive self-regulation and academic achievement. To date, the detrimental furnishings of psychologically controlling education on students' outcomes have been well-documented (Soenens et al., 2012; Haerens et al., 2015; Bartholomew et al., 2018), and in this study, nosotros will explore the role of psychological command toward knowledge transfer evolution in an SL context.

The present investigation focused on three key inquiry questions (RQs). First, how do students' perceived noesis transfer change during a 9-calendar week SL program (RQ1)? Second, are in that location different developmental patterns of perceived knowledge transfer across students (RQ2)? Third, we asked what factors affected students' perceived noesis transfer development (RQ3)? The get-go and second research questions are exploratory in nature. Since students' engagement varies across developmental stages of SL (Li et al., 2016; Guo et al., 2016b), we await to run into a fluctuation in students' perceived knowledge transfer in the current report. With different motivation, personalities, and prior experiences, students may too demonstrate different trajectories in perceived knowledge transfer over the SL plan of nine weeks. For RQ3, based on the literature we reviewed, we expected that mastery goal orientation would facilitate students' perceived cognition transfer development in SL, while perceptions of psychological control would hinder the process.

2. Materials and Methods

two.i. Participants

Participants in the study were undergraduates at a leading enquiry university in China. This university is well-known for teacher education, education scientific discipline, and bones learning in arts and sciences. Nosotros recruited participants from a psychology class entitled Psychology of Learning. The class is about fundamental concepts and empirical enquiry findings related to learning sciences. Students who enrolled in the course were contacted at the beginning of the semester and invited to participate in a 9-calendar week SL program embedded in the course. Out of the 111 students enrolled in the course, 96 students (75 females and 21 males) consented to participate in the research. All participants were sophomore students from the Department of Psychology. The inquiry procedures and educatee surveys were approved by the establishment'south ethical commission.

2.2. Procedures and Measures

Students learned various learning principles (due east.g., applied beliefs analysis, conditioning theory, and learned helplessness) in their regular classroom learning. During weekends, they worked in a group of four to interact with children with special needs. Although the overall goal of the SL activity was "applying the knowledge and skills learned from the course of Psychology of Learning to serve children with special needs," the specific SL goals and activities were determined by the undergraduates themselves and might vary beyond groups. For instance, 1 group may focus on education the child to express his/her needs using appropriate words, while the other group may aim to teach the kid to pass and grab a ball. Each service group had a supervisor who provided support during and afterward SL activities. Students wrote reflective journal entries immediately after each service activity. Students also completed a serial of questionnaires prior to and subsequently SL regarding themselves and their SL experiences.

ii.two.1. Perceived Knowledge Transfer

To investigate the development of noesis transfer during SL, students' perceived cognition transfer was assessed at eight time points. We asked students to written report their levels of noesis transfer in their weekly reflective journal entries. A single-item measure was used ("Delight rate to what extent you applied the knowledge you've learned into this calendar week's SL activeness"), with the scale ranging from 0 "none" to 4 "a lot." To ensure the validity of the self-report item, the first writer went over students' cogitating journal entries and found that students who had high scores (i.e., 3 or iv) on this item used more psychology terms and concepts in their reflective periodical entries. Furthermore, the sum of the eight perceived noesis transfer scores was positively associated with the overall perceived knowledge transfer score in their post-SL reflective journal entries (r = 0.51, p <0.001).

2.2.2. Mastery Goal Orientation

In the pre-SL questionnaire, we used the half dozen-detail Job Goal Orientation Scale (Midgley et al., 1998) to assess students' goal to develop their understanding and skills. The items were translated into Chinese and rated on a v-point calibration (1 = not at all true of me, v = very true of me). Sample items included: "I like school work that I'll learn from, even if I brand a lot of mistakes." Internal consistency reliability was adequate (Cronbach's alpha coefficient = 0.71).

2.ii.three. Perception of Psychological Control

In the mail-SL questionnaire, we assessed students' perceptions of psychologically controlling didactics behaviors from their supervisors using the seven-detail Psychologically Controlling Teaching Calibration (Soenens et al., 2012). We translated the items into Chinese and adapted to the service-learning context. College scores on the scale reflect a more controlling supervising way. Case items include the post-obit: "My supervisor frequently interrupts me," and "My supervisor is less friendly with me if I do not see things his/her way." Calibration points ranged from 1 "completely disagree" to 5 "completely agree." Internal consistency reliability was good (Cronbach'southward alpha coefficient = 0.93).

2.3. Analysis

To explore how students' knowledge transfer evolves during SL (RQ1), nosotros assessed their perceived knowledge transfer across eight fourth dimension points from Week half-dozen to 14 in an 18-week semester. Data from previous studies suggest that there are four developmental stages of student engagement during a nine-week SL programme (Guo et al., 2016b). Descriptive statistics of student perceived noesis transfer beyond viii time points confirms such stage classification. Therefore, we described the development of pupil perceived knowledge transfer using the four stages that identified from previous piece of work, namely the confusion and hesitancy stage (1st time), the enlightenment and enthusiasm phase (2nd and 3rd time), the fluctuation and adjustment phase (4th to 7th time), and the stabilization and routinization phase (8th time). Repeated-measures analysis of variance (ANOVA) was used to examine the fluctuations of perceived knowledge transfer across the 4 developmental stages. To further empathise the pattern of students' perceived noesis transfer development beyond students (RQ2), we conducted a model-based cluster analysis on students' perceived knowledge transfer beyond 4 developmental stages. The Bayesian information criteria (BIC) were considered to determine the optimal classification. After identifying the groupings of participants, repeated-measures ANOVA was conducted to exam the development of perceived knowledge transfer beyond groups. To explore the differences betwixt groups of students (RQ3), we conducted multinomial logistic regression to exam the associations between the predictors (i.due east., mastery goal orientation and psychological control) and the identified groups. Statistics were done using R version 4.0.2, the mclust (Scrucca et al., 2016), the nnet (Ripley et al., 2016), and the rstatix (Kassambara, 2020) packages.

3. Results

3.one. Students' Perceived Noesis Transfer Fluctuated Across Iv Stages of SL

Every bit shown in Figure one, students' perceived cognition transfer fluctuated beyond the whole SL program. Repeated measures ANOVA indicated pregnant differences in students' perceived knowledge transfer across the four stages [F _{(2.6, 246.98)} = viii.82, p <0.05, η² = 0.05]. Pairwise comparisons suggested that students' perceived cognition transfer significantly increased from Stage i to Stage ii (p <0.001). No meaning divergence was found between Stages 2 and 3, although nosotros observed a slight drop in the level of perceived knowledge transfer during Stage iii. students' perceived knowledge transfer rose to a loftier bespeak and peaked during the last stage of the 9-calendar week SL plan. students' perceived noesis transfer during Phase 4 was significantly higher than those in Phase 1 (p <0.001), suggesting that participating in the 9-week SL plan might foster students' perceived knowledge transfer.

Figure 1. Trends in students' perceived knowledge transfer during a 9-week service learning (SL) program. Mistake bars represent 95% confidence intervals.

3.two. The Pattern of Perceived Cognition Transfer Development Varied Beyond Students

Students' perceived noesis transfer scores across four stages were used in model-based cluster analysis for the categorization of groupings. Based on the all-time BIC values, the cluster analysis approach produced v clusters with 27 students in Grouping ane, 12 students in Group 2, 46 students in Group 3, four students in Grouping 4, and vii students in Group 5. We plant a significant interaction effect between time and group on students' perceived knowledge transfer, F _{(nine.36, 213)} = 8.32, p <0.001, η² = 0.xix. This result suggests that the developmental pattern of perceived knowledge transfer varied across groups of students. Effigy ii shows the developmental pattern of perceived cognition transfer for each group.

Effigy ii. Trends in students' perceived cognition transfer for different groups of students.

Group 1 deemed for 29% of the whole sample. Students in this group reported moderate levels of perceived knowledge transfer in Stage 1. At that place was a slight rise in perceived knowledge transfer from Phase 1 to 2; even so, information technology gradually decreased since Stage 2. Group ii accounted for fourteen% of the sample. These students demonstrated a loftier level of perceived cognition transfer at the first of the SL program; however, their perceived knowledge transfer steadily declined for the remainder of the programme. Group 3 deemed for the largest proportion (46%) of the sample. Perceived knowledge transfer score increased from Phase i to two. Although there was a slight driblet in Stage 3, it rebounded and peaked in the last phase of SL. Groups 4 and 5 accounted for vii and 4% of the sample, respectively. These two groups had similar patterns during Stages 1 and 2. Students had relatively low perceived cognition transfer scores at first. Then, the scores increased in Stage ii. Dramatic differences between Groups 4 and 5 were observed later on Stage ii. For Group iv, at that place was a steady pass up in students' perceived noesis transfer; in contrast, Grouping five's perceived cognition transfer increased sharply from Phase 2 to 3, and it maintained the same level until the end.

three.3. Trends in Students' Perceived Knowledge Transfer Were Associated With Students' Mastery Goal Orientation and Their Perceptions of Psychologically Controlling Behaviors From Their Supervisors

To further understand the differences amongst students in terms of their perceived noesis transfer development, we tested the predicting furnishings of perception of psychological control and mastery goal orientation on group membership (contour). Groups iv and 5 were excluded from the following analyses as the sample sizes of these 2 were limited. The results of multinomial logistic regression are shown in Table 1. Students who perceived more psychologically decision-making behaviors from their supervisors had college possibilities of membership in Grouping 1 relative to Group iii. Students with college scores of mastery goal orientation presented college possibilities of membership in Group 3 relative to Group 1.

Tabular array i. The results of multinomial logistic regression.

Groups one and 3 accounted for 75% of the whole sample. As shown in Figure 2, the major difference in the perceived knowledge transfer patterns between Groups 1 and three was observed between Stages 3 and iv. For Grouping 1, students' perceived knowledge transfer remained steady across the ii stages. In contrast, Group three demonstrated a marked increase in perceived knowledge transfer from Stage 3 to 4. Compared to Group 1, Group 3 showed a more than adaptive trend in perceived knowledge transfer. These findings suggest that higher students' perceived knowledge transfer development during a ix-week SL plan may be promoted by mastery goal orientation and impeded by perceptions of psychological control.

four. Discussion

Although the positive impact of SL on college students' noesis transfer has been well-established (Markus et al., 1993; Eyler and Giles, 1999; Deeley, 2010; Prentice and Robinson, 2010; Gerholz et al., 2018; Wang et al., 2019b), the developmental characteristics of knowledge transfer too equally the influencing factors have not been investigated. In the current study, we investigated how students' perceived knowledge transfer evolved within the context of a 9-week SL program and examined the impact of mastery goal orientation and perception of psychological control on this process. By providing testify of the dynamic procedure and mechanisms of students' perceived noesis transfer development, the present study contributes to our understanding of how, when, and why the benefits of SL are realized. It directly addresses calls for investigating the underlying mechanisms of how SL enhances student academic outcomes (Eyler, 2000; Furco et al., 2016).

Drawing upon the developmental stages identified in previous studies (Li et al., 2016; Guo et al., 2016b), we divided the nine-week SL program into four stages, namely the confusion and hesitancy phase, the enlightenment and enthusiasm stage, the fluctuation and aligning stage, and the stabilization and routinization stage. Despite these stages being initially identified to draw the characteristics of student engagement, the changes of perceived knowledge transfer across eight time points demonstrated the same pattern. This is not surprising because the link betwixt date and academic success has been consistently demonstrated in traditional learning contexts (Finn and Zimmer, 2012) as well as in SL (Wang et al., 2019b).

On the question of the development pattern of perceived knowledge transfer, we constitute that students' perceived cognition transfer in SL did not follow a linear trajectory. Although students' perceived knowledge transfer at the end of SL (i.e., Phase iv) was significantly higher than those at the beginning (i.eastward., Stage 1), a drop was observed in the middle of SL during Stage iii (4th to seventh time). The drop in perceived cognition transfer might exist related to the development of the SL activities. Afterward implementing and revising interaction plans several times, students started to establish routines for their SL activities during Stage 3. Rather than setting new goals or designing new interactive activities, students were more likely to brand minor modifications to their interaction plans. Although they nevertheless used the knowledge they learned from classes to serve children with special needs, students tended to underrate their levels of knowledge transfer equally the learning principles that were included in their interaction plans or activities were more often than not adopted from previous ones rather than newly added. The changes in SL activities may also explicate the rebound in perceived knowledge transfer during Stage four (8th time). In the last SL activities, students not only implemented their accustomed interaction activities but as well designed new activities to celebrate the end of SL with the recipients. Unlike behavior modifications, a cheerio celebration focuses on emotional communication and creating a relaxing atmosphere, which offers students opportunities to apply new noesis and techniques related to learning sciences.

Another of import finding was that the developmental blueprint of perceived knowledge transfer in SL varied across students. Although five groups were identified with model-based clustering, 75% of the students belong to Groups one and iii. The developmental pattern of perceived knowledge transfer for Group 3 is similar to the one for the whole sample. Despite a slight drop during Stage 3, students' perceived cognition transfer increased throughout the SL program. Students in Group 1 had a similar developmental blueprint as Group three between Stages 1 and 3; even so, their perceived cognition transfer did not option up during the final stage of the program. Compared to Group 1, students in Group iii demonstrated a more adaptive developmental pattern of perceived noesis transfer. The variability in college students' perceived cognition transfer development suggests that teachers should be mindful of students' cognitive and emotional states when implementing SL activities and provide them with distinct interventions.

Cartoon from two gimmicky motivation theories, we examined the associations of two social-cognitive variables—mastery goal orientation and psychological command—with patterns of perceived cognition transfer development. The present investigation contributes to our understanding of the social and cognitive factors influencing students' learning development when in SL contexts. The findings showed that students who perceived less psychological control from their supervisors and possessed college levels of mastery goal orientation had higher possibilities of membership in Group 3. That is, they were more than likely to demonstrate adaptive development patterns in perceived knowledge transfer during a 9-week SL program. Mastery goal orientation and psychological control play essential roles in affecting college students' perceived cognition transfer development and raise the question as to what strategies instructors may use to promote mastery goal orientation and finish existence psychologically controlling in the context of SL. Evidence from cocky-decision theory enquiry suggests a number of approaches, such as providing students with choices, acknowledging students' perspectives, providing meaningful rationales, avoiding controlling language (eastward.g., "should," "must," "take to"), and staying abroad from salient reward contingencies (Ryan and Deci, 2017). To foster students' mastery goal orientation, the TARGET framework (Ames, 1992) provides instructors with a toolbox of teaching strategies for creating mastery-oriented learning environments, such every bit focusing attention on students effort, not on abilities, de-emphasizing the negative effect of making errors, and helping students establish feasible, but challenging goals.

The current study has several limitations we should note. Outset, the findings are exploratory in that they represent student experiences within a unmarried SL program that was embedded in the form of Psychology of Learning. Equally such, the sample does not represent all fields and potentially over-samples students along gender lines. It would be benign to replicate these results in a variety of different types of courses and fields. 2d, students' perceived knowledge transfer was assessed with a single-particular measure. Although single-item measures generally perform well when gauging a holistic perception (Youngblut and Casper, 1993), every bit is the case hither, a multiple-detail measure would be necessary if researchers intend to obtain a better gauge of the construct. Third, it is intriguing that mastery goal orientation and perception of psychological command were associated with patterns of perceived knowledge transfer development; even so, there may be alternative influential factors based on other theoretical frameworks that future research needs to explore. Moreover, the findings virtually the changes in perceived noesis transfer need to be interpreted with caution, as we practice not accept a comparison group showing how students' perceived knowledge transfer evolves in a regular lecture-based learning context. Further quasi-experimental investigations are needed to make up one's mind the bear on of SL on the development of perceived knowledge transfer.

Information Availability Statement

The raw data supporting the conclusions of this commodity will be made available by the authors, without undue reservation.

Ethics Argument

The studies involving homo participants were reviewed and approved by Beijing Normal University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

CW and MY designed the written report. CW, FG, YL, and MY collected the data. CW and WY formulated the hypotheses. CW performed the statistical analyses and drafted the manuscript. CW, WY, FG, YL, and MY revised and edited the manuscript. All authors contributed to the article and canonical the submitted version.

Funding

This research was supported by the MOE Project of Key Research Plant of Humanities and Social Sciences at Universities (No. 15JJD190002).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We give thanks Yongjie Chen, Xiuping Yao, Chen Wang, Hui Ma, Hong Ma, Guoliang Pu, and Xiaoli Zong for their dedication to the SL program. Special acquittance to all of the SL providers and recipients in this study.

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