how motivation influences student engagement a qualitative case study

• Journal of Education and Learning
• Vol. 1, No. 2 (2012)

How Motivation Influences Student Engagement: A Qualitative Case Study

•   Sitwat Saeed    
•   David Zyngier    

The authors use Ryan and Deci’s (2000) Self-Determination Theory (SDT) to better understand how student motivation and engagement are linked combined with Schlechty’s Student Engagement Continuum to analyse the impact of intrinsic and extrinsic motivation on students’ different engagement types. The study seeks to understand which type of motivation – intrinsic or extrinsic – is more closely aligned to authentic student engagement as identified by Schlechty (2002, 2011). A qualitative research framework was adopted and data was collected from one elementary school class. According to Ryan and Deci’s SDT, the majority of students who indicated that their motivation type was either intrinsic or integrated regulated motivation also demonstrated that they were authentically engaged in their education (Schlechty, 2002, 2011). The students who preferred extrinsic motivation also showed ritual and retreatist forms of engagement and students demonstrating both intrinsic and extrinsic motivation showed authentic, ritual, retreatist and rebellious engagement. In line with findings by Zyngier (2008) in this particular study at least, when pedagogical reciprocity (Zyngier, 2011) was present, intrinsic motivation assisted authentic student engagement in learning, and that extrinsic motivation served to develop ritual engagement in students however, students who had both types of motivation showed different types of engagement in their learning.

• DOI: 10.5539/jel.v1n2p252

• ISSN(Print): 1927-5250
• ISSN(Online): 1927-5269
• Started: 2012
• Frequency: bimonthly

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How motivation influences student engagement: A qualitative case study

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T1 - How motivation influences student engagement: A qualitative case study

AU - Saeed, Sitwat

AU - Zyngier, David

M3 - Article

SN - 1927-5250

JO - Journal of Education and Learning

JF - Journal of Education and Learning

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How Motivation Influences Student Engagement: A Qualitative Case Study Journal of Education and Learning (2012) with Sitwad Saeed

2012, Journal of Education and Learning

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The authors use Ryan and Deci's (2000) Self-Determination Theory (SDT) to better understand how student motivation and engagement are linked combined with Schlechty's Student Engagement Continuum to analyse the impact of intrinsic and extrinsic motivation on students' different engagement types. The study seeks to understand which type of motivation – intrinsic or extrinsic – is more closely aligned to authentic student engagement as identified by Schlechty (2002, 2011). A qualitative research framework was adopted and data was collected from one elementary school class. According to Ryan and Deci's SDT, the majority of students who indicated that their motivation type was either intrinsic or integrated regulated motivation also demonstrated that they were authentically engaged in their education (Schlechty, 2002, 2011). The students who preferred extrinsic motivation also showed ritual and retreatist forms of engagement and students demonstrating both intrinsic and extrinsic motivation showed authentic, ritual, retreatist and rebellious engagement. In line with findings by Zyngier (2008) in this particular study at least, when pedagogical reciprocity (Zyngier, 2011) was present, intrinsic motivation assisted authentic student engagement in learning, and that extrinsic motivation served to develop ritual engagement in students however, students who had both types of motivation showed different types of engagement in their learning.

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How Motivation Influences Student Engagement: A Qualitative Case Study

The authors use Ryan and Deci’s (2000) Self-Determination Theory (SDT) to better understand how student motivation and engagement are linked combined with Schlechty’s Student Engagement Continuum to analyse the impact of intrinsic and extrinsic motivation on students’ different engagement types. The study seeks to understand which type of motivation – intrinsic or extrinsic – is more closely aligned to authentic student engagement as identified by Schlechty (2002, 2011). A qualitative research framework was adopted and data was collected from one elementary school class. According to Ryan and Deci’s SDT, the majority of students who indicated that their motivation type was either intrinsic or integrated regulated motivation also demonstrated that they were authentically engaged in their education (Schlechty, 2002, 2011). The students who preferred extrinsic motivation also showed ritual and retreatist forms of engagement and students demonstrating both intrinsic and extrinsic motivation showed authentic, ritual, retreatist and rebellious engagement. In line with findings by Zyngier (2008) in this particular study at least, when pedagogical reciprocity (Zyngier, 2011) was present, intrinsic motivation assisted authentic student engagement in learning, and that extrinsic motivation served to develop ritual engagement in students however, students who had both types of motivation showed different types of engagement in their learning.

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Saeed, S., & Zyngier, D. (2012). How Motivation Influences Student Engagement: A Qualitative Case Study. Journal of Education and Learning , 1 (2). https://doi.org/10.5539/jel.v1n2p252

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Examining the causal relationships between interpersonal motivation, engagement, and academic performance among university students

Takamichi ito.

1 Faculty of Human-Environment Studies, Kyushu University, Fukuoka, Japan

Takatoyo Umemoto

2 Faculty of Foreign Studies, Kyoto University of Foreign Studies, Kyoto, Japan

Associated Data

All relevant data are within the paper and its Supporting Information files.

This study investigates the validity of path models in which interpersonal motivation positively predicts behavioral, emotional, and cognitive engagement, and behavioral engagement positively predicts superior performance in collaborative learning in university classes. The path model was tested using structural equation modeling. The results of the analyses showed that weak positive paths from identified regulation to all three aspects of engagement were substantial. In addition, a weak positive path from intrinsic motivation was significant for emotional engagement. For performance, the weak positive path from behavioral engagement was statistically significant. Based on these results, the implications of the motivation theory and practice in higher education are discussed.

Introduction

Understanding the autonomous motivation for human interaction in collaborative learning is important for guiding engagement in collaborative activities in the classroom, leading to superior performance. To date, a vast body of research in the educational context has demonstrated that intrinsic motivation is a strong and positive predictor of academic achievement and performance [ 1 – 4 ]. In addition, a number of theoretical and empirical examinations have been accumulated in research on motivation in academic learning, and, as a result, these research findings [ 5 – 7 ] have revealed that intrinsic motivation for learning positively predicts academic engagement and that engagement is a key factor mediating intrinsic motivation and academic performance.

However, previous studies have primarily focused on how intrinsic motivation for individual learning as a personal factor positively influences engagement in academic learning by each person. The classroom is a place for individual learning, as well as for learning with classmates. Interest in and value placed on learning content are important motivational factors, but the kinds of motivations they have for interpersonal relationships in learning situations may also be relevant. To examine the process of academic achievement in collaborative learning in detail, it is necessary to address interpersonal motivation; however, such studies have not been found to any great extent.

Self-determination theory and interpersonal motivation

Self-determination theory [ 3 , 6 ] is a major motivational theory that elaborates on intrinsic and extrinsic motivations and clarifies specific functions of multiple motivations. Self-determination theory proposes four types of motivations in order of the degree of self-determination. The first is external regulation, which refers to motivation through rewards, punishment, or coercion from others. The second is introjected regulation, which stems from feelings of shame and anxiety and motivates behavior to maintain self-esteem. The third is identified regulation, in which motivation is based on the perceived value or importance of the behavior. The fourth is intrinsic motivation, which is spontaneous motivation generated by interest, fun, and enjoyment. These different types of motivations are positioned on a continuum of self-determination. In other words, intrinsic motivation has the highest level of self-determination, while external regulation has the lowest.

Previous research [ 4 , 8 ] based on the self-determination theory has often examined motivation for learning in the academic domain. As research has progressed, studies have been conducted to examine motivation not only in the academic domain, but also in the human relations domain. For example, studies have addressed motivation for prosocial behavior [ 9 ] and examined friendship motivation [ 10 , 11 ]. Motivational factors such as prosocial and friendship motivation have been shown to influence psychological adjustment and individuals’ well-being.

Prosocial and friendship motivation are important aspects of motivation, but considering the collaborative learning situations that are common in classrooms, it may be necessary to look at motivation for group activities. However, from the perspective of the self-determination theory, there has been little research on interpersonal motivation in collaborative activities. Although intrinsic motivation has been considered the strongest predictor of behavior in previous studies, identified regulation has also been shown to play an important role in a variety of contexts [ 12 , 13 ].

Motivation, engagement, and educational outcome

Regarding motivation for individual learning, many studies [ 5 , 6 ] have shown that intrinsic motivation positively determines behavioral, emotional, and cognitive engagement in educational contexts. Walker, Greene, and Mansell [ 7 ] have investigated whether intrinsic motivation, identification with academics, and self-efficacy predict cognitive engagement among college students. The results of the path analysis indicated that intrinsic motivation, identification with academics, and self-efficacy positively predicted cognitive engagement. Although the study was conducted on junior high school students, Shih [ 14 ] has reported the following results based on self-determination theory: students who learned from personal interest and personal relevance, that is, intrinsic motivation and identified regulation, were more emotionally and behaviorally engaged in schoolwork. Jang [ 15 ] has examined the relationship between rationale, motivation, behavioral engagement, and conceptual learning during relatively uninteresting learning activities among undergraduate students; structural equation modeling analysis found significant positive paths from identified regulation to behavioral engagement, and then from behavioral engagement to performance [ 15 ]. Furthermore, Saeed and Zyngier [ 16 ], through a qualitative case study, have suggested that students with high intrinsic motivation were authentically engaged in their education. As in the previous studies presented above, regarding motivation in individual learning as a personal factor, intrinsic motivation and identified regulation positively determine behavioral, emotional, and cognitive engagement. Similar associations can be assumed in interpersonal motivation of learning situations that require collaboration with others. It is possible that individuals who are motivated by enjoying and valuing interpersonal relationships may be more willing to actively engage in collaborative learning in behavioral, emotional, and cognitive aspects.

Furthermore, previous research has shown that intrinsic motivation and identified regulation lead to a variety of educational outcomes, including academic performance. For example, intrinsic motivation and identified regulation have been found to be positively associated with academic achievement [ 12 ], well-being, and school adjustment [ 13 ]. In addition, recent studies have shown that identified regulations have more desirable educational outcomes than intrinsic motivation. For example, in a longitudinal study, Otis, Grouzet, and Pelletier [ 17 ] found that identified regulation was more strongly positively associated with educational adjustment (i.e., dropout intentions, absenteeism, homework frequency, and educational aspirations) than intrinsic motivation. Koestner and Losier [ 18 ] conducted a longitudinal study of academic satisfaction after entering college. The results revealed that intrinsic motivation and identified regulation positively predicted academic satisfaction in the early years, but only identified regulation predicted academic satisfaction in the long run. In addition to these studies, a review of over 40 years of research and a meta-analysis of studies on the undermining effect [ 2 ] have shown that intrinsic motivation predicted more unique variance in quality of performance. Although the above studies include findings of individual motivation for learning and activity, it can be assumed that interpersonal motivation would show similar predictions for performance through collaborative learning. Therefore, individuals who are motivated by greater interest and importance in interpersonal relationships will be more willing to engage in academic work with their classmates. This will result in superior performance through collaborative learning.

Academic engagement and performance

Academic engagement has been demonstrated by several educational studies as a key variable that is a direct and strong predictor of performance [ 19 – 21 ]. Engagement is defined as a student’s active involvement and emotional quality during a learning activity [ 22 ]. Engagement has been validated by previous studies in three dimensions: behavioral, emotional, and cognitive [ 5 , 23 , 24 ]. Behavioral engagement includes effort, attention, and persistence while participating in the learning activities [ 21 ]. Emotional engagement includes enthusiasm, interest, and enjoyment [ 21 , 25 ]. Cognitive engagement refers to how students use sophisticated in contrast to superficial learning strategies [ 26 ]. Prior research has shown that all three types of engagement are positively associated with academic performance, but path model testing has shown that behavioral engagement, in particular, is a significant positive predictor of academic performance [ 27 – 29 ]. Behavioral engagement is the process of paying attention to a learning task itself. As such, it is assumed to be most directly linked to learning outcomes.

Collaborative learning is a significant educational experience from primary and secondary education to higher education [ 30 – 32 ]. Previous research suggests that engaging in collaborative and cooperative learning can lead to academic achievement [ 30 , 33 , 34 ]. Active engagement in classroom situations, including collaborative learning, will lead to a deeper understanding of the lecture, creative thinking, and better performance in university classes.

Current study

Based on the findings of previous studies and the presented review, the hypotheses of this study are summarized as follows.

• Identified regulation and intrinsic motivation will positively predict behavioral, emotional, and cognitive engagement.
• Behavioral, emotional, and cognitive engagement will positively predict academic performance.
• Among the three aspects of engagement, behavioral engagement will be the strongest positive predictor of academic performance.

In examining these hypotheses, because engagement is a psychological factor for an individual that is deeply grounded in the actual situation, we will attempt to examine the extent of engagement in university classes that incorporate collaborative learning. In light of previous research [ 19 – 21 ], engagement in the classroom leads to better performance. Performance is measured by the extent to which students show a profound understanding and creative thinking in their essays. Based on the findings of previous studies [ 5 – 7 ], a path model can be postulated in which identified regulation and intrinsic motivation positively predict behavioral, emotional, and cognitive engagement, and behavioral engagement positively predicts superior performance in university classes. This hypothetical structural equation model is illustrated in Fig 1 below. This study empirically investigates the validity of such causal models to obtain suggestions for theory and practice in higher education.

Note: The bold arrow indicates the strongest association.

Participants

The participants of this study were 363 Japanese undergraduate students (223 male, 124 female, and 16 non-respondents) in their second through fourth years of college. The average participant age was 19.37 ( SD = 1.26) years old. This study was approved by the research ethics committee of the Faculty of Human-Environment Studies at Kyushu University (approval number 2019–006). The research was conducted according to the guidelines for human subjects and verbal informed consent from the participants was obtained.

Interpersonal motivation for collaborative learning

To assess interpersonal motivation for collaborative learning, we distributed a questionnaire face-to-face to participants before the lecture. Based on Okada [ 10 ], Ryan and Connell [ 9 ], and Vallerand and Blssonnette [ 8 ], we developed an interpersonal motivation questionnaire to assess the four motivational concepts of external, introjected, identified, and intrinsic reasons for establishing human relationships in collaborative learning. The subscale used to assess each concept was composed of four items; therefore, this motivation scale comprised a total of 16 items. Regarding interpersonal relationships in daily collaborative learning, participants were asked, “Why do you want to be close to or spend time with your group members?”

An example of an external regulation item for this question is “Because I am asked by those around me to build relationships with my members”; of introjected regulation is “Because I feel anxious if I am not close to group members”; of identified regulation is “Because it is important for me to spend time with group members”; and finally, of intrinsic motivation is “Because it is fun to spend time with group members.” Details of the questionnaire items are given in the S1 File . These items were presented on a Likert scale with responses ranging from “1” for “I don’t agree at all” to “5” for “I agree very much.” Scoring was based on responses from 1 to 5, and these scores were used for subsequent analyses. The same is true for all subsequent measurements.

Immediately after the lecture, including pair work and collaborative learning, we measured behavioral, emotional, and cognitive engagement. Based on Reeve and Tseng [ 28 ] and Skinner, Kindermann, Connell, and Wellborn [ 5 ], a questionnaire with three aspects of engagement was developed. Behavioral engagement consisted of five items (e.g., “I paid attention in pair work,” “I tried very hard in pair work”). Emotional engagement consisted of five items (e.g., “When we work on something in pair work, I felt interested,” “Pair work was fun”). Cognitive engagement consisted of four items (e.g., “I devised the way to promote learning through pair work,” “I devised the way to deepen the ideas in the discussion through pair work”). Details of the questionnaire items are provided in the S1 Appendix . These items were presented on a 1–7 bipolar response scale, with responses ranging from “1” for “not at all true for me” to “7” for “very true for me.” Scoring was based on responses from 1 to 7, and these scores were used for subsequent analyses.

Performance

After the pair work, the students were instructed to think individually and write a report while exercising their creativity and reflecting on the content of the dialogue with their partners. A worksheet (one sheet of A4 size) was distributed, with a column for writing each of the three questions (corresponding to about one-third of the paper space). Based on the essay content, which should be three to five lines long, the students were graded on a scale of A to C. According to the order of rating, the highest grade, A, was scored as three points, while grade C was scored as one point considering the quality and depth of thought. The report was ranked “C” when there was: “lack of explanation,” “mere description of the lecture content as it is,” or “insufficient consideration.” A report that met the following criteria was ranked as “B”: “the explanation of the lecture content includes one’s own ideas,” “original consideration by the author,” and “new information is added to the lecture content.” Rank “A” was scored when: “In addition to one’s own opinion, one’s partner’s ideas are included in the discussion in a valid way,” “One’s own ideas are contrasted with those of one’s partner, and novel ideas are formed,” “Based on the dialogue, a deep discussion is created.”

The first author explained the grading criteria in advance and two graduate students majoring in educational psychology independently graded the reports. Ten reports were randomly selected, and two graders were checked to ensure that they fully understood the grading criteria. Subsequently, another 100 descriptions were randomly selected for further grading, with an inter-rater agreement rate of 76.67%. Reports with inconsistent grades were carefully discussed by the first author and two graders, and the final grades were determined. After confirming that a common understanding of the grading criteria had been obtained, the two raters graded the remaining reports separately.

The classroom practice in this study was conducted in the traditional “lecture” style with more than 100 students. This study was conducted in two classes, both of which were lecture courses in the field of psychology at universities. The content of the two lectures included an overview of “what is intelligence,” “development of new intelligence theories,” “intelligence and academic achievement,” and “metacognition and learning.” The 90-minute class was divided into three sessions, and 30 minutes per session was planned as the approximate time allocation. Each session consisted of 20 minutes of lectures, five minutes of pair work, and five minutes of individual report writing. At the beginning of the lecture, students were asked to pair up freely with classmates near their seats. During the pair work and collaborative learning, the roles of the speaker and listener were alternated halfway so that the interaction did not become one-sided. Themes for discussion of lecture content were presented to encourage dialogue in pairs. Subsequently, we introduced the theme of the report based on the dialogue that involved creative thinking. While writing the essay, the students were asked to quote the ideas expressed by their partners and describe them in an original way. The flow chart of the experimental process is shown in Fig 2 .

Evidence based on internal structure

Confirmatory factor analysis was conducted to examine the factorial validity of each scale. A four-factor structure for interpersonal motivation and three-factor structure for engagement were assumed and verified. The parameters were estimated using the maximum likelihood method. The goodness of fit was as follows: for interpersonal motivation, χ 2 (84) = 429.397, p = .000, χ 2 / df = 5.112, RMSEA = .108, 90% CI [.098, .118], SRMR = .089, CFI = .859, TLI = .823; and engagement, χ 2 (74) = 258.925, p = .000, χ 2 / df = 3.499, RMSEA = .084, 90% CI [.073, .096], SRMR = .041, CFI = .949, TLI = .937. The indicators of the two scales had satisfactory values. Factor loadings were higher than .537 for all scales.

Reliability coefficients were calculated for the four types of interpersonal motivation and three aspects of engagement. One external regulation item was deleted because of its low reliability. As shown in Table 1 , these values were approximately satisfactory. There were three sessions in this class and each student wrote three reports. The reliability coefficients were calculated based on three reports, and the values were approximately satisfactory.

Next, the composite reliability (CR) values were calculated, which are shown in Table 1 . These values were approximately satisfactory. In addition, to examine the convergent validity of the scales, average variance extracted (AVE) values were also calculated. As shown in Table 1 , these values were approximately satisfactory.

Following prior studies, the mean values of the items were calculated for each subscale of interpersonal motivation and engagement, and the scale scores were used in the following analyses. The average score of the three reports was calculated and used as an index of performance. The means and SD s of each scale score are presented in Table 1 .

Evidence based on relations between conceptually related variables

To examine the construct discriminant validity of the scales, the AVE square root of each construct was calculated. As shown in Table 2 , the results were approximately satisfactory.

* p < .05.

** p < .01.

*** p < .001.

Note: Italicized numbers represent the AVE square root of each construct.

The results of calculating the correlation coefficients between interpersonal motivation, engagement, and performance are presented in Table 2 . A simplex structure was identified among the four kinds of interpersonal motivation, as assumed by self-determination theory. In a continuous sequence from external to internal regulation, adjacent variables showed significant positive correlations (e.g., identified regulation and intrinsic motivation). There was also a significant negative correlation between distantly located variables (e.g., external regulation and intrinsic motivation). There were also significant weak to moderate positive correlations among all three aspects of engagement.

Regarding the correlation between interpersonal motivation and engagement, there was a rather weak but significant negative correlation between external regulation and behavioral and emotional engagement. There was a significantly weak positive correlation between the identified regulation and the three aspects of engagement. In addition, there was a significantly weak positive correlation between intrinsic motivation and the three aspects of engagement. Finally, for performance, there was a fairly weak but significant positive correlation with identified regulation, behavioral engagement, and emotional engagement.

Analysis of path model

We hypothesized a path model with interpersonal motivation as the antecedent, through engagement, and ultimately to determine performance, which was verified by structural equation modeling. Missing values were processed using the full information maximum likelihood method. The fit indices of the model were satisfactory, with χ 2 (18) = 20.139, p = .325, χ 2 / df = 1.119, RMSEA = .018, 90% CI [.000, .052], SRMR = .028, CFI = .998, and TLI = .996. The results of these analyses are presented in Table 3 and Fig 3 .

** p < .01. *** p < .001. Note: Statistically significant paths are shown as solid lines with path-coefficient estimates.

Following the path flow, the statistically significant paths, in order of causality, were as follows. First, the weak positive paths from identified regulation toward all three aspects of engagement were substantial. Second, a weak positive path from intrinsic motivation was significant for emotional engagement. Finally, for performance, the weak positive path from behavioral engagement was statistically significant.

Examining path models

The assumed causal model was verified using structural equation modeling. Based on the order of causal direction, the paths that were significant are discussed in turn.

As predicted, there were significant positive paths from identified regulation to behavioral, emotional, and cognitive engagement. Previous research [ 12 , 13 ] has shown that identified regulation has a positive influence on academic achievement and school adjustment, which is consistent with the results of this study. In the first study to assess interpersonal motivation for collaborative learning, the role of identified regulation was shown to be especially important. This is a novel finding. Future research should include interpersonal motivation as an important antecedent factor in elucidating the learning process in classes that include collaborative learning.

By contrast, intrinsic motivation showed a significant positive path only for emotional engagement. Emotional engagement includes interest and enjoyment and intrinsic motivation consists of similar emotions. Intrinsic motivation was assessed before the lecture and was similar to the trait construct. Emotional engagement assesses the psychological state of the students while they are engaged in the class and is a construct that is more likely to change depending on the situation. Intrinsic motivation, a relatively stable antecedent, positively predicted emotional engagement, which is a situational factor. Behavioral and cognitive engagement were not related to intrinsic motivation, but this may be due to differences in psychological aspects. The scale items for intrinsic motivation used in this study were limited to questions examining emotional (e.g., fun, pleasant, delightful) rather than behavioral or cognitive aspects. Further verification is required in the future.

As hypothesized, a positive association was found between behavioral engagement and performance. This finding is consistent with previous reports [ 27 – 29 ]. Semester grades and final exam scores have often been used as indicators of performance, but this study revealed that performance was predicted by an index of creative and critical thinking writing based on classroom dialogues.

All path coefficients were found to be positive and significant, but the values were generally small. Possible reasons for this result are as follows: first, the scale of interpersonal motivation measured the tendency to be motivated in daily collaborative learning situations. The three dimensions of engagement were measured immediately after the lecture, in the context of the current situation; therefore, different levels of measurement could have weakened the association between these variables. Second, engagement was a measure based on self-evaluation, whereas others’ evaluations were used to measure performance. These differences in evaluators may have weakened the association between engagement and performance. Essentially, there may be some difficulty for engagement to produce educational outcomes in collaborative learning situations that require interaction with others. In particular, the performance tasks in this study required deep thinking and high creativity through dialogue with a classmate, which may not have been easy.

Implications for educational practice and limitations of this study

As the hypothesized causal model was verified, the following practical suggestions were considered. First, university educators need to support identified regulation among other interpersonal motivations. It is important to encourage university students to realize the value and importance of interacting with others through cooperative learning, and to provide them with such experiences. Once students identify with the value of interpersonal relationships, identified regulation leads to behavioral, emotional, and cognitive engagement, which in turn leads to active participation in university classes, including collaboration. Focused attention and persistence in deep thinking through dialogue with classmates results in superior performance.

In addition, university educators should help students find fun and excitement in interacting with others through collaborative learning. If students are intrinsically highly motivated beforehand, they can enjoy and become interested in university classes that involve collaboration. As there were high positive correlations between engagement in the three behavioral, emotional, and cognitive dimensions, there may be potential for changes in engagement in other aspects as well.

Although the internal correlations of engagement are significant, it is necessary to keep in mind that behavioral engagement is particularly important in relation to performance and learning outcomes. Instructors are required to create a learning environment that allows students to focus on and sustain their attention and actively participate in collaborative learning. Following the path model, the necessary practices can be summarized as follows. First, educators should encourage students’ identified regulation and intrinsic motivation. In the classroom, students should create a learning environment that allows them to engage behaviorally. As this psychological learning process unfolds, students can think and learn deeply and creatively based on their dialogue with their classmates.

In recent years, research on teaching and learning has focused on self-regulated [ 35 – 38 ] and socially shared regulation of learning [ 39 – 42 ]. While it is important for students to learn by self-regulating their own cognitive and motivational processes, it is also necessary for them to learn by regulating each other’s cognition and motivation through collaboration and dialogue. Interpersonal motivation and engagement in collaborative learning should be deeply related to socially shared regulation of learning, and future research is required to examine this in more detail.

The limitations of this study are as follows. First, the study was conducted at a single university, which decreases the likelihood that findings are generalizable. Second, the assessment of engagement in this study examined active participation in classroom situations, including collaborative learning. Two aspects of engagement must be distinguished and demonstrated: engagement in collaboration with classmates and engagement in personal thinking and writing activities. Third, in this study, collaboration was through dialogue between pairs. However, there can be a variety of teaching styles and techniques that promote cooperative learning [ 30 , 33 , 43 ]. It is necessary to further verify the results by changing the cooperative learning method, group size, and task content.

Conclusions

Using structural equation modeling, this study validated a path model from interpersonal motivation through engagement to superior performance. We were able to apply interpersonal motivation to collaborative learning situations and clarify the process of its influence. This is the novelty and significance of this study, and provides a possibility for future research. From the perspective of motivation, this study suggests a new direction for university classes and learning processes.

Supporting information

S1 appendix, acknowledgments.

We would like to express our gratitude to all of the university students and graduate students who cooperated in our research.

Funding Statement

This research was supported by JSPS KAKENHI Grant Numbers JP17K04352 and JP20K03337.

Data Availability

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Doctoral Dissertations and Projects

A qualitative collective case study investigating the motivational factors of elementary-aged students in physical education class and leisurely physical activity.

Jesse Tanner Beam

School of Education

Doctor of Education (EdD)

Judy Sandlin

Childhood Obesity, Motivation, Physical Education, Positive Reinforcement

Disciplines

Education | Elementary Education and Teaching | Health and Physical Education

Recommended Citation

Beam, Jesse Tanner, "A Qualitative Collective Case Study Investigating the Motivational Factors of Elementary-Aged Students in Physical Education Class and Leisurely Physical Activity" (2015). Doctoral Dissertations and Projects . 1011. https://digitalcommons.liberty.edu/doctoral/1011

The purpose of this qualitative collective case study was to increase understanding of the influential motivating factors of elementary-aged students in physical education (PE) that foster positive reinforcement to manage student engagement. The study was conducted at three different elementary schools in a school district in the southeastern United States. To determine the factors that influence the students' motivation in PE and leisurely physical activity, a set of data collection sources was used. Student interviews, caregiver surveys, and teacher journal entries were utilized to collect purposeful data that identified the specific factors associated with participation. Data was then transcribed and coded to identify reoccurring themes across the cases. The study found multiple factors associated with PE engagement and leisurely physical activity involvement, which are: (a) incentives play a role in motivation; (b) organized and leisurely physical activity foster positive relationships among peers; (c) bullying negatively affects students' motivation; (d) leisurely family activities foster higher engagement levels in children; (e) access to parks, recreational facilities, and youth sports leagues play a role in leisurely physical activity levels; (f) caregivers' involvement in their child's education allows communication between teacher and caregiver to strengthen the PE program; (g) the effectiveness of the classroom management of the teacher ensures all students are provided with an education that is safe and fair; (h) the teacher's ability to use incentives appropriately increases the likelihood of the most desirable behaviors; and (i) consistent school-wide application of the PBIS model reinforces positive student outcomes.

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Article citations More>>

Saeed, S. and Zyngier, D. (2012) How Motivation Influences Student Engagement: A Qualitative Case Study. Journal of Education and Learning, 1, 252-267. https://doi.org/10.5539/jel.v1n2p252

has been cited by the following article:

TITLE: Relationship between Locus of Control and Academic Achievement of Secondary School Students in Abia State

KEYWORDS: Locus of Control , Attribution , Academic Achievement , Motivation

JOURNAL NAME: Journal of Analytical Sciences, Methods and Instrumentation , Vol.11 No.2 , June 30, 2021

ABSTRACT: The study intended to determine the relationship between locus of control and academic achievement of secondary school students. Some students have been observed to achieve higher while some achieve lower even after being exposed to the same subject matter by the same instructor. The objective of the study was to determine if locus of control correlated with academic achievement of students as moderated by gender and school-type. The study was anchored on attribution theory. The study adopted a correlational research design. A total of 388 SS3 students in Aba Education zone were selected using purposive and simple random sampling techniques. Instruments for data collection were an adopted LOC scale and students’ exam scores in Mathematics, English and CRS. To determine the reliability of the instrument, Kuder-Richardson reliability test (KR-20) was employed and an overall coefficient of 0.76 was obtained for LOC scale. Data were analyzed using Pearson Product Moment Correlation Coefficient. Results showed significant relationship between locus of control and academic achievement of male students. Results also showed significant relationship between locus of control and academic achievement of public school students. Based on the findings, it was recommended that school authority should encourage good performance by rewarding students with excellent performance, because when good behaviour is rewarded, the individual is motivated to do better. Also, government should also provide the schools with necessary infrastructures that would make teaching and learning very interesting.

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• Published: 11 June 2024

Perception of enhanced learning in medicine through integrating of virtual patients: an exploratory study on knowledge acquisition and transfer

• Zhien Li 1 ,
• Maryam Asoodar 1 ,
• Nynke de Jong 2 ,
• Tom Keulers 3 ,
• Xian Liu 1 &
• Diana Dolmans 1  

BMC Medical Education volume  24 , Article number:  647 ( 2024 ) Cite this article

Metrics details

Introduction

Virtual Patients (VPs) have been shown to improve various aspects of medical learning, however, research has scarcely delved into the specific factors that facilitate the knowledge gain and transfer of knowledge from the classroom to real-world applications. This exploratory study aims to understand the impact of integrating VPs into classroom learning on students’ perceptions of knowledge acquisition and transfer.

The study was integrated into an elective course on “Personalized Medicine in Cancer Treatment and Care,” employing a qualitative and quantitative approach. Twenty-two second-year medical undergraduates engaged in a VP session, which included role modeling, practice with various authentic cases, group discussion on feedback, and a plenary session. Student perceptions of their learning were measured through surveys and focus group interviews and analyzed using descriptive statistics and thematic analysis.

Quantitative data shows that students highly valued the role modeling introduction, scoring it 4.42 out of 5, and acknowledged the practice with VPs in enhancing their subject matter understanding, with an average score of 4.0 out of 5. However, students’ reflections on peer dialogue on feedback received mixed reviews, averaging a score of 3.24 out of 5. Qualitative analysis (of focus-group interviews) unearthed the following four themes: ‘Which steps to take in clinical reasoning’, ‘Challenging their reasoning to enhance deeper understanding’, ‘Transfer of knowledge ‘, and ' Enhance Reasoning through Reflections’. Quantitative and qualitative data are cohered.

The study demonstrates evidence for the improvement of learning by incorporating VPs with learning activities. This integration enhances students’ perceptions of knowledge acquisition and transfer, thereby potentially elevating students’ preparedness for real-world clinical settings. Key facets like expert role modeling and various authentic case exposures were valued for fostering a deeper understanding and active engagement, though with some mixed responses towards peer feedback discussions. While the preliminary findings are encouraging, the necessity for further research to refine feedback mechanisms and explore a broader spectrum of medical disciplines with larger sample sizes is underscored. This exploration lays a groundwork for future endeavors aimed at optimizing VP-based learning experiences in medical education.

Peer Review reports

In Medical Education, a persistent challenge lies in the bridge between acquiring theoretical knowledge and applying it in real-world clinical scenarios. Many medical students struggle with translating their classroom learning into practical settings. The primary challenge lies in effectively translating the concepts students have learned into authentic patient interactions. This gap is particularly concerning because it affects the quality of patient care, as medical students are not just learning to acquire knowledge but must be able to apply this knowledge in complex healthcare settings.

One approach to address this challenge is the use of Virtual Patients (VPs), a computer-based simulation of real-life clinical scenarios for students to train clinical skills [ 1 ]. Research has shown that using VPs in the classroom can effectively improve various aspects of learning, from core knowledge and clinical reasoning to decision-making skills and knowledge transfer [ 2 , 3 , 4 , 5 ]. The VPs provide students with the opportunity to practice skills in a safe and controlled simulation environment.

Recent studies have focused on optimizing the design and arrangement of VPs as part of learning activities to facilitate both knowledge acquisition and retention [ 6 , 7 , 8 ]. For instance, Verkuyl, Hughes [ 8 ] demonstrated that using VPs as gamification tools can improve students’ confidence, engagement, and satisfaction.

However, studies focusing on the specific factors that contribute to these improvements when integrating VPs into the classroom are limited, particularly in understanding how to use VPs in the classroom to facilitate the transfer of knowledge students’ gain from the class to the subsequent studying stage of their education and eventual practice.

Acquisition and transfer of knowledge are critical factors in medical education, as medical students must be able to apply their knowledge and skills to real-world clinical scenarios [ 9 ]. Research suggests that for the effective transfer of knowledge, students should be immersed in authentic environments, enabling the transition of learned competencies to advanced stages [ 10 , 11 , 12 , 13 ].

Despite the consensus on the efficacy of VPs as a tool, there is a gap in understanding how to integrate VPs in the classroom to optimize students’ learning, especially in facilitating learning transfer. The effectiveness of VPs is not just in their use but also in how they are used by students to enhance their understanding on how to reason and make decisions about medical treatments when dealing with clinical cases. Without a clear and deep understanding, we risk underutilizing their potential and losing opportunities for medical students to become well prepared for real-world clinical scenarios.

Certain elements, such as role modeling instruction [ 14 , 15 , 16 ], using various authentic cases [ 17 , 18 , 19 ], and engaging in peer discussions on feedback [ 20 , 21 , 22 ], emerge as potential key components that could be integrated to maximize the knowledge acquisition via VPs. For instance, Stalmeijer, Dolmans [ 23 ] show how an expert, serving as a role model, provides guidance that facilitates student learning by demonstrating clinical skills and reasoning out loud. While there is ample evidence supporting the advantages of inclusion of VPs in education, there is not enough research focusing on the detailed aspects of effective instructional design techniques. This paper delves into these components, seeking to understand how the VP integration influences students’ learning and knowledge transfer. Figure  1 shows the theoretical framework of how integrating VPs in class affects students’ learning and might impact the transfer of learning in a simulated VP environment to practice.

Relationship of implementing, impact factor, and transfer of training

This exploratory study aims to investigate how instructional design elements such as role modeling, various authentic cases, and peer dialogues on feedback within VP sessions affect students’ learning from the learner’s perceptions. The core research question in this study focuses on how the implementation of role modeling, various authentic cases, and peer dialogue on feedback in VPs, influences learners’ perception of knowledge gain and transfer in personalized medicine.

The study was conducted at Maastricht University in the elective course, “Personalized Medicine in Cancer Treatment and Care”. This course is open to second-year undergraduate medical students of Maastricht University.

Participants

Initially, 24 students enrolled in this course for the academic year of 2022–2023, and 22 students participated in the Virtual Patient session. In total, 19 students voluntarily completed the survey designed to evaluate their experiences and perceptions of the Virtual Patients session. Thereafter, 9 of the 19 survey respondents voluntarily agreed to participate in three focus group interviews, with 2–4 students in each focus group. Students were informed that participation in this research study had no impact on student’s academic performance or their continuation in their studies.

Intervention

The instructional approach for the VP cases was structured in a specific format for the students. Figure  2 shows the instructional design for VP integration. The first stage was a role-modeling phase, where an expert demonstrated the clinical reasoning process using VP Case A. This was followed by a practice session where students worked in pairs on two different VP cases (Case B and C). After that, students formed two larger groups each including 5 or 6 students, and discussed the system feedback that was provided by VP platform. Finally, the expert summarized the session and addressed students’ questions. The whole intervention lasted 120 min. Figure  1 gives an overview of the intervention steps.

The flow of integrated virtual patient session

1. Role modeling (30 min): The intervention started with an expert, a clinician with teaching experience, demonstrating a clinical case (Case A) and showing the clinical reasoning process by thinking aloud. The expert served as a role model in showcasing the approach toward clinical problem-solving, provided supportive information, and demonstrated how to proceed through the case. The aim of the role modeling session was to empower students to apply the insights and methodology gained from experts in case A to solve subsequent cases (case B and case C), Although these cases shared similarities in underlying principles, they diverged on patient characteristics such as age, complications, and smoking history that can influence patient treatment outcomes.

2 and 3. Two VP pair tasks (20 min each): In this segment, the 22 participating students were paired, resulting in 11 pairs. These pairs were then divided into two groups. Group 1 (6 pairs) and group 2 (5 pairs) alternated in going through Case B and Case C to account for the practice effect. These cases were variations of the clinical cases introduced during the role-modeling demonstration, differing in patient characteristics such as age, complications, and smoking history to challenge the students’ reasoning. Students were encouraged to work collaboratively.

4. Feedback discussion (30 min): Upon completion of the VP cases, an automated feedback is immediately provided about the reasoning analysis. Participants were instructed to save this feedback for later discussion. After that, Students were organized into groups of six, based on the sequence in which they engaged with the cases. For instance, those who first practiced with Case B and then proceeded to Case C formed Group (1) Conversely, students who started with case C and then moved on to case B were assembled into Group (2) To foster meaningful dialogue, students engaged in discussions focused on the feedback generated by the Virtual Patient system, guided by a printed discussion guide distributed to each group (see Appendix 2 ). The discussion aimed to deepen students’ understanding and enrich their conversations about the cases they had just completed.

5. Plenary (15 min): This part lasted 15 min. Hosted by the expert to summarize the session and address questions or doubts raised by students.

During the practice and discussion sessions, the expert circulated among the groups to offer additional guidance and support.

The virtual patient cases

Three Virtual Patient (VP) cases (Case A, B, and C) were created to enhance students’ comprehension of specific concepts, knowledge, and skills in clinical reasoning. The VP practice was developed on the P-Scribe ( www.pscribe.nl ) learning platform, a web-based e-learning system based in the Netherlands. The platform facilitates the design and implementation of text-based VP sessions (Appendix 4 ).

While these cases shared a foundation on authentic head and neck cancer treatment, they were characterized by varying patient characteristics in terms of age, gender, and medical history (anamnesis).

VP case flow chart

Within each VP case, students were presented with a scenario related to neck cancer. Figure  3 shows the chart of a VP case. Each case starts with an overview of the patient and their medical history which students had to use to make an initial assessment. After this, students encountered a mix of multiple-choice and open-ended practice questions. These questions guided students in planning diagnostics, formulating a diagnosis, and devising a treatment plan tailored to the patient’s specific needs. Immediate feedback was provided after students submitted each response, and comprehensive summative feedback was given at the conclusion of each case to foster understanding and learning from any potential misjudgments or oversights (See Appendix 4 ).

Measurement instruments

Learning-perception survey : The survey (Appendix 1 ) consisted of 20 items, structured into five primary sections: general experience, intended learning outcome, role modeling, practicing with various authentic cases, and reflection on peer dialogue around feedback. The first item asked about students’ general experience through the whole session. The second item focused on their perception of intended learning outcomes. Six items then focused on the students’ perceptions of learning through role modeling followed by 5 items addressing perceptions related to their learning on practicing with authentic cases. The final seven items explored students’ perception of learning from dialogue around feedback. Participants indicated their level of agreement for each statement using a 5-point Likert scale: 1 denoting “Strongly Disagree”, 2 for “Disagree”, 3 for “Neutral”, 4 for “Agree”, and 5 for “Strongly Agree”. For interpretation, average scores below 3 were considered as “in need for improvement”, those of 4 or higher as ‘good’, and those between 3 and 4 as ‘neutral’.

Focus group interviews : Three focus group interviews (Appendix 3 ) were conducted to dive deeper into students’ perceptions of their learning experience, knowledge gain, and knowledge transfer in real-world settings. The focus group took place after the survey and the survey data did not affect the development of the focus group questions. In focus group 1, two students, in focus group 2, two students and in focus group 3, five students participated. The interviews were structured around a series of questions that explored students’ perceptions of their learning across specifically designed sections. These sections included Role Modeling, Practice with Various Authentic Cases, and Dialogue around Feedback. The structure aimed to understand students’ perspectives on each key component of the learning sections.

The analysis of the survey data was conducted by calculating the mean, standard deviation, and the Alpha Coefficient for the responses pertaining to each of the five key dimensions of the survey. The mean score provided an indicator of the average student perception, while the standard deviation offered insights into the variability of the responses. The Alpha Coefficient, a measure of internal consistency, was computed to assess the reliability of the survey dimensions. Through these statistical measures, an overall understanding of the students’ perceptions regarding the various aspects of the Virtual Patients was attained, facilitating a robust analysis aligned with the research objectives.

The focus-group interview data were analyzed following the thematic analysis procedure set out by Braun and Clarke [ 24 ]: (1) familiarize yourself with your data, (2) generate initial codes, (3) search for themes, (4) review themes, (5) define and name themes, and (6) produce the report. The interview was guided by pre-existing frameworks or theories in medical education. This ensured the capture of major aspects of the VP learning experience as underscored in the existing literature: role modeling, using various authentic cases, and peer dialogue around feedback [ 16 , 17 , 18 , 20 , 21 ]. The focus group interview was recorded, transcribed, and coded by three team members and ordered in initial themes (Z.L, M.A, and X.L). These themes were discussed with the larger team. We used a process of inductive and deductive analysis and used the three design principles of role modeling, practice with various authentic cases, and group discussion on feedback as sensitizing concepts to study the data [ 24 ]. Thereafter, quantitative and qualitative analyses were collectively appraised, compared, and checked for inconsistencies. In this triangulation, the themes identified in focus-group interviews were explanatory to the descriptive statistics of the survey.

Trustworthiness

Several measures were taken to enhance the study’s trustworthiness. First, triangulation was achieved by employing multiple data collection methods, including surveys and focus group interviews. The interview data collection continued until saturation was reached, ensuring a comprehensive understanding of the student’s experiences and perceptions. Secondly, the coding process followed an iterative approach. Team members initially coded transcripts independently, and then met to reach a consensus before moving on to code subsequent transcripts. Three researchers conducted the coding independently to minimize bias and enhance the validity of the findings. Finally, a member check among a sample of the focus group interviewees was conducted. In response to the question asking whether they agreed with summaries of preliminary results and would provide comments, confirmatory responses were received as well as some minor additional comments and clarifications. The latter were taken into account in the analysis and interpretation of the data.

Ethical approval

The Maastricht University Ethical Committee reviewed and approved this study. The approval number is FHML-REC/2023/021.

The findings from both the survey data and focus group interviews were presented to explore students’ perceptions of the effectiveness of the Virtual Patient (VP) Session in enhancing their clinical reasoning skills.

Survey data

The survey explored students’ perceptions across five key dimensions: General Experience, Intended Learning Outcome, Role Modeling, Practicing with Various Authentic Cases, and students’ reflection on Peer Dialogue around Feedback. The students scored the VP sessions on 20 items (Table  1 ). The scores varied between M = 2.95 to M = 4.58, on a scale of 1–5.

For the General Experience of Virtual Patient Session (Items Q1-Q2) the average score was M = 4.13 (SD = 0.70). Specifically, the overall experience was positively rated at M = 4.11. The component that assessed the improvement of clinical reasoning skills received an average score of M = 4.16.

Regarding the Students’ Perception of Learning from Role Modeling (Items Q3-Q8), the average score was M = 4.38 (SD = 0.61). Students agreed that the expert demonstration at the start of the session helped them understand the intended learning outcomes and was useful in guiding them through the Virtual Patient cases, with scores ranging from M = 4.26 to M = 4.58.

Students’ perception of learning from practicing with various authentic cases (Items Q9-Q13), received an average score of M = 4.00 (SD = 0.86). The scores measured the students’ perception of how well the provided Virtual Patient cases matched their current level of understanding, enhanced their comprehension of the subject matter, and helped them grasp the complexities inherent in real-world clinical scenarios.

For their perception of learning from Peer Dialogue around Feedback (Questions 14–20), the average score was M = 3.24 (SD = 1.05). These scores measure the students’ perception of the effectiveness of peer dialogue in enhancing understanding, generating strategies to address feedback, and prioritizing areas of improvement.

Focus group interview data

The interviews revealed five themes: ' Which steps to take in clinical reasoning’, ' Asking challenging questions to enhance deeper understanding of knowledge’, ‘The variety in cases helps to enhance transfer to the real world’, and ‘Deeper understanding of reasoning through reflections’.

Which steps to take in clinical reasoning

Students acknowledged the expert’s initial demonstration helped them to develop structured knowledge and gain understanding of the clinical reasoning process.

I think it (Role modeling) helps to find a pattern in clinical reasoning as well. At first, it (the expert) explained to us. For example, are there possible lymph nodes? Yes or no. Then you need to do this and this…Then you can make kind of…pattern that differs for the diagnosis and the prognosis. So you can make kind of a diagram in your head. Which you can use later on. And your knowledge becomes more structured. (Focus Group 2, Student B)

Students also perceived that the integrated practice with Virtual Patients helped them to anticipate the subsequent steps in clinical reasoning. They indicated the patterns learned through practicing with virtual Patients helped them understand the procedures they needed to follow to evaluate the patient.

I think now I know the steps which they (the procedural) followed to evaluate the patient, so first we can do this and then that. First, you determine the TNM (Tumour, Node, Metastasis) staging and do the endoscopy, then the TNM staging, and then you make the treatment plan. Now it’s more clear how they do those steps. (Focus Group 1, Student A)

Moreover, students thought the pair work and dialogue helped them think and clarify with each other what steps they needed to do in clinical reasoning when they had different opinions.

Yeah, that (pair working) was really nice because you can discuss, like I think do this and the other one says, you know, I think do that step, and then you’re already discussing the answers which is really nice to have. (The discussion) really make you think about the steps. (Focus Group 1, Student b)

Challenging their reasoning to enhance deeper understanding

Students reported how the course design differed from other blocks. According to the students, the VP practice was particularly beneficial in helping them integrate knowledge, and make the knowledge their own.

It (the VP practice) helps you to integrate knowledge because other blocks are really only lectures, they are all listening and listening. So the virtual patient was really nice to make this stuff our own. (Focus Group 2, Student A)

Students indicated the examples given by the expert helped them get a better understanding of the more detailed TNM (Tumor, Node, Metastasis) table, that are used in clinical reasoning.

Yeah, she (the expert) gave examples and guided the reading of the tables for TNM (Tumor, Node, Metastasis) staging, and those were also in the Virtual Patient cases, but because she already used them once and explained how we have to use them, it became more clear to us, what these tables are for and how they are used (Focus Group 1, Student B) .

The students noted that in VP practice sessions, compared with passive learning in traditional lectures, they were challenged to engage directly with the material by making clinical decisions, such as selecting appropriate tests to reach a diagnosis.

In lectures, we passively learn the trajectory from symptoms to diagnosis. During Virtual Patient practice, we actively process it. So you have to make decisions and select the test etc. (Focus Group 2, Student B)

Students indicated that practicing with the VP cases challenged them to look up information and reasoned by themselves. They gave an example of the imaging practice in which they were tasked with examining specific body parts in medical images on their own, they thought they were challenged to reason about what they saw instead of getting the information directly.

Yeah, also the (medical) imaging in the assignments where you need to look at a specific part of the body, normally you just see a picture and someone says, yeah, this is the stomach or this is the heart, whatever, and now you need to look it up yourself and think about it yourself, what you see, so that really helps. (Focus Group 1, Student B)

Furthermore, they emphasized the questions asked by experts challenged them to think, put the knowledge in their own words and apply the knowledge with their own reasoning.

The questions she (the expert) asked really make you think about the things she’s learning(teaching). So if she asks questions, you’re really thinking, and yeah, you’re challenged to put it in your own words. (Focus Group 1, Student B) For instance, she (the expert) asked questions that not from official guidelines, instead, it came from where widely doctor worked and her personal experiences. I applied what she said with my own reasoning behind it. (Focus Group 2, Student B)

Transfer of knowledge

Students perceived that practicing with VP cases in different situations offered them hands-on experience, where they actively engaged with various situations, which prepared them for future patient interactions.

Having cases that are closer to the real world, like the comorbidity we discussed, would make it more realistic. (For instance, ) What if he also has obesity or diabetes? Those are the patients that we are going to see in the future. So it helps out a lot to have those different conditions as well. (Focus Group 2, Student B)

Students also indicated their preference for the structured approach of the VP session, where an initial demonstration by an expert, sharing their clinical experience, followed by hands-on practice with VP cases was perceived to enhance transfer to practice. This method, as described by the student, bridged the gap between theoretical knowledge and practical application. They think this structure made the knowledge clear and further helped them to transfer their knowledge from theory to practice.

You (the Virtual Patient session that integrated with role modeling, authentic VP practice, and peer discussion around feedback) made it (the clinical reasoning) clear for me because of the first case we discussed with the teacher. Well, he discussed it and showed us how to think, and how to get things from certain perspectives with risk factors, age, et cetera. And then we do it ourselves. We had to find out what was wrong and go on. So I quite liked it. It gave me a deeper understanding. (Focus Group 3, Student A)

Students indicated the sense of practical immersion is amplified by the “side information that you don’t really need” (Focus Group 3, Student E) from the cases. They highlighted the side information represented the interaction with real patients and made them think of clinical situations in real-world settings.

(Side) information would be more realistic, also side information that you don’t really need because a patient also tells you a lot of things, and some of those things aren’t as important, but you still need to decide if they are important or not. What do you see, why do you see it, what’s different than normal. (Focus Group 3, Student E)

Moreover, several students indicated that the hypothetical “what-if” discussions during the role modeling session helped them with reasoning, prompting them to consider complications that might arise in real-life medical situations.

So for example, about age, it’s more difficult to do a treatment above 70. (What if that patient) has things like smoking history and that kind of stuff. I think it’s really valuable because you have already had an example about it (Demonstrating Case A). (Focus Group 1, Student A)

Students indicated that the diagnosis practice in VP led them to realize the difference in real-world scenarios. They said while in the simulated environment might seem easy to choose multiple diagnostic options, in the real world, medical professionals must make more selective decisions due to limitations. They think this experience taught them to think of prioritizing and decision-making in a realistic medical setting.

Yeah, maybe also there (in VP cases) were also a question about which imaging techniques you would use and then it was Echo or CT, MRI, there was also an option where you could listen to the lungs and some of the people also checked that one, but it isn’t really necessary, so you think it only takes one minute, so why not, but in the real world there isn’t always time to do everything, so it’s also good to think what is really necessary and what’s not. (Focus Group 1, Student A)

Enhance reasoning through reflections

During the VP session, students received feedback and conducted conversations around the feedback provided by the Virtual Patient system. Students thought the peer dialogues around feedback provided opportunities for collective reflection and insights, allowing them to pinpoint areas of improvement.

I thought that (the peer dialogue) was really useful, because sometimes one person, for example, when the teacher explains everything, you don’t pick up everything he says. She (your peer) might pick up a different thing, and I pick up a different thing, and we can ask each other, do you know how this works? So I thought that was really useful. (Focus Group 3, Student B)

The students emphasized the importance of expressing and discussing different opinions. They noted that such interactions could provide new insights and perspectives that they would not have considered independently, thereby enriching their understanding.

When you do have different opinions, I think they (your peers) can give you insight that you maybe didn’t have for yourself. So you can add to each other’s knowledge. If somebody has another view, then we can discuss it. It (the discussion) brightens my tunnel view. Also having to say it (the knowledge) out loud and explaining your thoughts to someone else can also help, I think. (Focus Group 2, Student A)

When talking about the peer dialogues around feedback during the VP session, Some students highlighted the benefits of immediate feedback, which provided them with clarity and instant validation. However, others saw value in delayed feedback, as it fostered discussion and multiple interpretations.

I liked that the Virtual Patient program, that it gave you immediate feedback. That was really handy. And I also liked the discussion afterward so we could speak about it a bit more (Focus Group 3, Student B) . There was immediate feedback on most questions, so you knew if you had been correct or wrong. But for the learning process it might be handy to have that after the group discussion, because now we all have the same answer. (Focus Group 2, Student B)

The study demonstrated the perception of students’ learning and knowledge transfer by integrating VP cases with role modeling introductions, and peer dialogue around feedback, specifically in the context of personalized medicine in cancer treatment and care. The survey reflected a positive learning experience and students reported they gained a better understanding of the clinical reasoning process as well as which steps to take when dealing with a clinical case through this specific course design with integration of VP cases. Qualitative data showed that the integration of VPs into the educational setting clearly shifted the students from being passive observers in a traditional lecture-based format to active participants in a simulated clinical environment. This shift is in line with previous research findings, which suggest that the use of VPs in clinical training actively engages learners and encourages the application of their knowledge [ 4 ].

The quantitative data revealed that students highly valued the role modeling session, as indicated by the high average scores. Qualitative data explained that the role modeling session enabled students to not only observe the clinical process being demonstrated but also to engage in active thinking by interacting with the expert. As discussed by Cruess, Cruess [ 15 ], role modeling not only consciously imparts knowledge but also unconsciously influences students’ attitudes and behaviors, making the learning experience more relatable to the clinical environment. In this study, by sharing clinical reasoning and personal anecdotes during the class, experts made the learning experience more relatable to the clinical environment that students would face in the future. This mirrored the role modeling research by Morgenroth, Ryan [ 25 ] which emphasizes the importance of role models in shaping the self-concept and motivation of individuals. Moreover, the qualitative data showed that the demonstration by the expert serves as a fundamental pre-knowledge for students to cover the knowledge gap and prepare them with the following practice. This finding aligns with van Merrienboer’s scaffolding concept emphasizing the importance of initial expert guidance in learning processes [ 16 ].

Followed by the role modeling demonstration, students practiced on two VP cases in pairs and perceived that the VP practice enhanced their clinical reasoning skills, and also helped them understand the real-world clinical setting. The result showed that the variety and real-life complexity of cases in the VP sessions were perceived to be essential for students’ knowledge gain and transfer. The positive perception of various authentic cases aligns with previous research highlighting the importance of exposure to diverse and authentic scenarios in medical training [ 17 , 18 ]. Moreover, the hypothetical “what-if” scenarios further enhanced students’ analytical abilities, preparing them for the multifaceted challenges they would encounter in real-world medical situations. Survey responses (Q10, mean = 4.37; Q13, mean = 4.05 in Table  1 ) indicated a consensus among students on the improvement with this practice in understanding and applying knowledge. Our findings corroborate with Jonassen and Hernandez-Serrano [ 26 ]’s study emphasis on the importance of authentic learning environments for effective knowledge transfer.

After the practice, students discussed the feedback provided by the VP system. Despite its mixed quantitative reception, the peer dialogue on feedback was qualitatively found to be a vital component for promoting critical thinking, discussion, and reflection. The Feedback from the VPs, both immediate and delayed, along with peer dialogue, emerged as crucial elements in students’ learning process. In this study, students showed different preferences for receiving feedback. Some students preferred immediate feedback, however, others preferred delayed feedback. How feedback was provided notably influenced peer interactions. Given that immediate feedback was dispensed upon submission of answers, the peer dialogues automatically started when students noticed disparities or encountered obstacles. Such dialogues not only served to resolve ambiguities but also fostered collective reflection, enhancing comprehension of the subject. By vocalizing their thoughts and engaging in active discussions, students were able to solidify their understanding and uncover nuances they might have missed otherwise. This aligns with the importance of engaging in peer discussions on feedback as outlined in the theoretical background [ 20 , 21 , 22 ].

When looking at the integration of VP cases with the particular course design, students perceived that the expert demonstration, followed by VP practice, and peer dialogue around feedback fostered a comprehensive understanding, allowing them to integrate diverse clinical knowledge, which in turn promoted understanding. The “Watch-think-do-reflect” structure not only ensured better knowledge retention but also enhanced students’ enthusiasm towards the subject. Observing model demonstrations enabled students to assimilate clinical nuances and contemplate real-world applications. Subsequent hands-on practice with VP cases fortified their cognitive structures, honing their clinical reasoning. Ultimately, students perceived that reflective peer discussions on feedback solidified their learnings, enhancing knowledge retention.

Limitations

This study employed a survey and focus group interviews that provided a comprehensive understanding of students’ perceptions of learning. However, there are several limitations. The study had a small sample size and was conducted in the context of an elective course, which may limit the generalizability of the findings. Furthermore, the study was exploratory in nature and did not measure actual learning outcomes or long-term retention, which are critical aspects of educational impact.

Implications for future research

Future research should investigate whether integrating Virtual Patients (VPs) into classroom activities enhance student learning outcomes by incorporating learning assessments and involving larger and more diverse participant groups to validate our findings. Additionally, a deeper analysis of students’ reasoning processes and interactions could provide insights into how and why knowledge gain and transfer are fostered or hindered. Furthermore, it is also important to understand the most beneficial moment for integrating VPs into educational settings to enhance transfer from a simulated to a real practice setting. This understanding could inform the development of more effective educational strategies and interventions.

The integration of Virtual Patients into classroom learning appears to offer a promising approach to enrich medical education. Key elements such as role modeling and various authentic cases contribute positively to students’ perception of learning, as well as peer dialogue on feedback. However, the approach to peer dialogue on feedback may need to be refined for more consistent benefits. Furthermore, studies with larger sample sizes and broader participant groups are essential to provide robust support for the efficacy of this educational approach and its components.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Thanks to all the participants and education workers who contributed to the study. ZL was supported by a scholarship granted by the China Scholarship Council. Thanks for the support of my family, and thanks Ang Li for joining our family.

ZL was supported by a scholarship granted by the China Scholarship Council (CSC, 202208440100).

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ZL, MA, DD, and NJ conceived of the presented idea. MA and DD verified the analytical methods. TK and ZL contribute to the creation of learning materials. ZL analyzed the data and drafted the manuscript under the supervision of MA and DD. All authors contributed to the article and approved the submitted version.

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Li, Z., Asoodar, M., de Jong, N. et al. Perception of enhanced learning in medicine through integrating of virtual patients: an exploratory study on knowledge acquisition and transfer. BMC Med Educ 24 , 647 (2024). https://doi.org/10.1186/s12909-024-05624-7

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DOI : https://doi.org/10.1186/s12909-024-05624-7

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How Motivation Influences Student Engagement: A Qualitative Case Study.

• S. Saeed , D. Zyngier
• Published 26 November 2012
• Education, Psychology
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