Effects of Personal Relevance on Learning Enjoyment
Hillary Ho Mei Yen
National University of Singapore
Abstract
The effect of personal relevance on learning enjoyment was investigated using a biological psychology task on brain anatomy. Participants were given 5 min to study specific brain parts and their functions. Based on the condition assigned, they were asked to describe how they, their mother or President Halimah would have used them. Personal relevance and learning enjoyment scales measured how personally relevant they perceived the material to be, and their level of enjoyment after doing the task. Inclusion of other in self (IOS) scale was a manipulation check for personal relevance. Results revealed significant main effects of condition on learning enjoyment and personal relevance, whereby participants with higher personal relevance reported greater learning enjoyment.
General Audience Summary
Research has shown that learners retain information better when they relate study material to themselves and apply it to their own lives, also known as the self-referencing effect (Hartlep & Forsyth, 2000). This potentially stimulates other benefits like learning enjoyment, which boosts one’s motivation and desire to learn. In this research, we show how learning personally relevant information would elicit greater learning enjoyment in the context of biological psychology.
As humans, we naturally attribute greater significance to self-relevant memories. As such, if we simply memorized facts and figures without feeling connected to them, they would be less significant, and therefore, less enjoyable to us. Our study found that participants who applied the usage of brain parts to themselves, reported greater learning enjoyment as compared to those who applied the usage of it to close others (e.g. mother) or distant others (e.g. president halimah).
These results challenge the way learning is projected in classrooms and prompts us to reconsider how learning can be contextualised in relation to self. Instead of the traditional method of powerpoint slides and worksheets, educators should aim to cultivate students’ passion and interest in the subject, which begins from enjoyment. Future applications can consider taking learning beyond classrooms, for instance, visiting different malls to learn about monopolies and oligopolies in macroeconomics.
Does Personal Relevance enhance Learning Enjoyment?
Over the years, we have memorised a great deal of mathematical formulas and scientific facts, which makes us wonder how these knowledge could benefit us in reality. Many students perceive learning as a mundane process for academic achievement rather than self-enrichment (Vaessen et al., 2017). This presents an educational problem where students do not enjoy learning, because they cannot relate to the subject personally, especially for abstract topics like biology and mathematics. Without a meaningful purpose, students may display a lack of enthusiasm towards learning (Krishnan, 2013). As a result, the lack of learning enjoyment reduces intrinsic motivation to learn.
To tackle this issue, we investigated and found support for the use of personal relevance as a potential approach in enhancing learning enjoyment. Specifically, students who had applied learnt material to themselves indicated greater learning enjoyment than those who applied the material to a familiar and distant other. This finding poses implications for promoting students’ learning enjoyment, which influences self-initiated learning and subsequent academic achievement.
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Personal Relevance (PR)
Learning enjoyment is derived from meaningful learning, where students find material applicable and relatable to themselves (Kuh, 2016). This is known as personal relevance, which is defined as the connectedness of a subject with students’ “out-of-school experiences” (Afari et al., 2013). This refers to the extent to which content taught in the classroom is relevant to students’ lives outside of school. Personal relevance encompasses the self-referencing effect which entails relating new information to one’s self or self-schema. Self-referencing effect on academic achievement is demonstrated by Barney(2007), who implemented a constructivist narrative assignment for psychology students. Students were required to write a paper, giving examples on how psychological theories were relevant to their own lives. Students who wrote the assigned papers reported superior writing quality, better grades and higher learning efficiency, thus suggesting that self-referencing produces beneficial learning outcomes.
Furthermore, Kelly et al. (2002) investigated the degree of self-referencing with three conditions – self-relevant vs other-relevant vs case judgment. Participants were required to make judgments about trait adjectives in relation to the self, for e.g. “Does this adjective describe you?”, others e.g. “Does this adjective describe George Bush?” and case judgment e.g. “Is this adjective in uppercase letter?” In essence, they found that participants in the self-relevant condition recalled more trait adjectives than participants in the other and case conditions, thus demonstrating a superiority effect of self-referencing on memory. Biological evidence also supports this reasoning, as fMRI scans revealed higher brain activation in the medial prefrontal cortex, which is preferentially engaged during self-referential judgments. Hence, these findings suggest that self-relevant information is typically learnt better than other-relevant information.
Learning Enjoyment (LE)
However, the direct effect of personal relevance on learning enjoyment has not been extensively studied in existing literature. Learning enjoyment is defined as the positive, activating and pleasurable emotions that one experiences in an activity (Ainley & Ainley, 2011). Imperatively, the value of learning enjoyment has been documented in both child and adult learners (Lucardie, 2014). Learning enjoyment is crucial in stimulating creativity and interest in young children, resulting in the popularity of games as teaching and learning tools. Similarly, enjoyment in the form of fun and laughter has been found to create conducive environments for adult engagement and deep learning (Lucardie, 2014).
In school contexts, research studies found learning enjoyment to be positively associated with higher motivation and better grades (Villavicencio & Bernardo, 2013) as it drives sustained interest in a subject (Tin & SpringerLink, 2016). Learning enjoyment also cultivates a mastery goal orientation, buffering the effects of failure which are inevitable in the learning process. (Tulis & Ainley, 2011). Students who enjoy the subject more tend to adopt mastery goals and persist in spite of failure, as opposed to students who do not enjoy the subject. Given these benefits, it is essential to examine how learning enjoyment can be further promoted within school environments.
Collectively, some studies have found positive effects of personal relevance on learning enjoyment. For instance, Aldridg, Afari & Fraser (2013) established direct and indirect pathways of personal relevance on learning enjoyment. Student participants who perceived mathematics as personally relevant e.g. “Maths is applicable to my life outside college” reported greater enjoyment in studying mathematics and being in math class. Incidentally, the same students also reported an increase in academic efficacy (i.e. confidence in academic ability), which predicts positive engagement, leading to increased learning enjoyment.
In addition, Pekrun’s (2006) control-value theory of achievement emotions suggests personal value to be a crucial predictor of enjoyment. Personal value comprises of achievement and domain values which are personally relevant components. Achievement value constitutes beliefs about the importance of achievement (e.g. attaining good grades is important for my future) while domain value consists of beliefs that drive intrinsic learning (e.g. learning philosophy broadens my understanding about life) Control-value theory proposes that perceiving high personal value on study material will elicit greater learning enjoyment in achievement contexts such as examinations. Specifically, individuals who possess high domain value apply studied material to everyday life, and would therefore enjoy learning more than individuals who are low on domain value. Based on this theory, Ainley ; Ainley (2011) measured the personal value of science among 15 year old students. They found that personal value positively predicted enjoyment of learning science, thus establishing a relationship between personal relevance and learning enjoyment.
Interpersonal closeness (Inclusion of Others in Self – IOS)
The present study measures personal relevance by the degree of interpersonal closeness (IOS scale) that individuals feel towards close and distant others. PR and IOS are studied together due to their similarities and complementary differences. By definition, both constructs consist of the “self” aspect, but IOS specifically refers to the inclusion of others within the self. This means that one’s self-identity is susceptible to change on the basis of attachment to significant others. To feel something is relevant, one needs to feel a sense of relatedness and affiliation, which is derived from interpersonal relationships with others (Zandvliet, 2014). During childhood and adolescence, we internalize the beliefs and orientations of close others like our parents and teachers, as identity development takes place (Santrock, 2016). As we mature, our identity stabilizes, causing the “others” aspect to distant from the “self” as we now developed unique personalities and interpretations of the world. Hence, while PR appears to be a self-driven construct, its foundations were laid out in early interpersonal relationships, allowing us to form a stable self and decide what we feel is personally relevant through introspection.
Correspondingly, PR and IOS differ in their central focus. PR emphasizes on applicability of learning to real world contexts (Afari et al., 2013) while IOS centres on the attachment bonds with other individuals (Aron, Aron & Smollan, 1992). As social beings, we possess an innate drive for attachment with similar individuals (Nitulescu, 2016). Therefore, our perception of personal relevance is moderated by social influences, such as the people we associate with, making PR and IOS complementary constructs, because the interpersonal aspects determine how relevant or important one perceives learning to be.
The Present Study
With this background, the present study employed a subset of biological psychology, (brain parts and functions), which required learners to relate these material either to themselves, their mother or president halimah. Biological psychology was chosen as it involves complex terminology, similar to mathematical equations, which students find a chore to learn. Personal relevance was primed to different degrees, with the self condition being the most personally relevant, followed by mother, then halimah. This allowed us to examine the self-referencing effect of personal relevance beyond trait adjectives (Kelly et al., 2002), which are commonly used in existing literature. In all, the present study hypothesizes that individuals with higher personal relevance will experience greater learning enjoyment (i.e. self > mother >halimah).
Method
Participants
Sixty-nine undergraduate students from the National University of Singapore (NUS), Singapore Management University (SMU) and Nanyang Technological University (NTU) were recruited on a voluntary basis. No incentives were given. However, three participants did not follow instructions, and another three did not match the criteria for this experiment, as they were working adults and psychology majors. These six data were excluded from all analyses. From the remaining sixty-three participants, thirteen participants’ data were excluded due to contamination. After removing thirteen outliers, the remaining fifty participants’ data were used for analysis. 15 were male, 35 were female, ranging from 20-26 years old (M=22.98, SD = 1.32). The racial distribution consisted of 46 Chinese , 1 Malay, 2 Indians and 1 Others. The students came from the following faculties: Arts and Social Sciences, Mathematics, Dentistry, Law, Medicine, Science, Architecture, Engineering, Computer Science and Business. There were no significant differences between race, gender and age before and after excluding the thirteen outliers.
Materials
Personal relevance (PR). To elicit varying degrees of PR, three variations of the same questionnaire was used. (Appendix B). They consisted of the same questions but differing subject of interest – “Write down one experience where you previously used your cerebellum vs where your mother would have previously used her cerebellum vs where President Halimah would have previously used her cerebellum.” Recalling a specific persona reinforces their personal relevance or lack thereof according to how close they felt towards their mother or President Halimah.
Learning Enjoyment (LE). Ten items measured (Appendix B) participants’ LE in relation to PR. Participants rated LE statements on a five-point Likert scale (1= Strongly Disagree, 5= Strongly Agree), with higher scores indicating greater LE. All ten items were adapted from the Academic Emotions Questionnaire (Pekrun, Goetz, Titz ; Perry, 2002). Reliability of the scale was found to be acceptable (? =.864).
Manipulation check (MC). Six items from the Constructivist Learning Environment Survey (Taylor, Fraser ; Fisher, 1997) were adapted to measure participants’ degree of personal relevance to the subject matter presented to them (Appendix C). The items serve as MC for personal relevance and the scale was found to be reliable (? =.762). In the other-related conditions (i.e. mother and halimah), the Inclusion of Others in Self (IOS) Scale (Aron, Aron & Smollan, 1992) (Appendix E) was used to measure participants’ personal relevance in relation to interpersonal closeness between self and mother, and self and halimah. Participants rated closeness on a seven-point Likert scale (1 = not close at all, 7 = extremely close).
Performance change. Pre-intervention and post-intervention tests (Appendix A and F) were administered to assess participants’ prior knowledge and knowledge gained thereafter. Performance change was measured as a side variable, and operationalized as: Post-test – Pre-test scores. Test scores were graded according to a scoring rubric which awarded points for certain key words and phrases (Appendix G). For instance, if participants mentioned key words like “perceiving emotions” – Amygdala or “addiction” – Nucleus accumbens, they would be awarded one point for it. The maximum marks attainable for each brain part is two.
Design and Procedure
A one-way fully between-subjects design was used. The main independent variable (IV) of interest was Personal Relevance (PR) with three levels – Self (1), Mother (2) and President Halimah (3). The dependent variable was Learning Enjoyment (LE). Participants were randomly assigned to one of the three conditions prior to the experiment. All of them underwent three experimental phases individually, consisting of the pre-intervention test, intervention and post-intervention test. Biological Psychology (brain anatomy) was used as the primary study material. Only non-psychology majors were recruited to avoid ceiling effects (e.g. everyone scores full marks) and floor effects (e.g. everyone scores poorly) in test scores.
At the start, participants underwent the pre-intervention test (Appendix A), where they were presented with a list of five brain parts and were asked to tick those that they knew the functions of. Subsequently, they were tasked to briefly describe the functions of respective brain parts that they have chosen. However, this section was automatically skipped for participants who did not tick any brain part, which also meant that they possessed zero prior knowledge of brain functions. During the intervention, participants were shown five study slides illustrating various brain parts – Cerebellum, Thalamus, Hippocampus, Amygdala, Nucleus Accumbens and their accompanying functions (see Appendix B). Participants in all three conditions were shown the same brain diagrams and function description. They were given five minutes to study each slide and write down an experience linking to the use of that relevant brain part.
After five minutes, participants were automatically directed to the next slide. Participants in condition one were asked to draw links to the self, while participants in condition two were asked to draw links to a close other (i.e. mother) and participants in condition three were asked to draw links to a distant other (i.e. Halimah). Thereafter, participants were required to complete the Personal Relevance Questionnaire, in which they indicated on a 5-point Likert scale, the extent to which they agreed or disagreed with personal relevance statements, e.g. ” After reading the slides, I learnt about the world outside of school” (1=Strongly Disagree; 5=Strong Agree). This assessed their level of personal relevance towards the learning of brain parts. Context specific phrases like “human brain” were incorporated into the original scale to fit the study’s context. Negatively worded questions, such as ” What I learnt has nothing to do with my out-of-school life” were reversed coded. Later on, they were required to complete the Learning Enjoyment Questionnaire which measured their enjoyment levels after studying the brain functions. They indicated on a 5-point Likert scale, the extent to which they agreed or disagreed with learning enjoyment statements, e.g. “I look forward to studying about the brain” (1=Strongly Disagree; 5=Strong Agree).
Next, participants in the mother and halimah conditions also responded on a 7-point Likert scale (IOS) which measured the degree of closeness between self-mother and self-halimah. (1=not close at all, 7=extremely close) Participants in the self condition did not undergo the IOS scale, as it was impossible to measure how close participants felt towards themselves. Lastly, participants in all conditions underwent the post-intervention test (Appendix F), where they were tasked to recall information that was learned in previous slides. Following which, participants’ demographics, such as their age, gender, university and school were collected. They were also asked to guess the hypothesis of this study.
Results
The following analyses are based on fifty participants. Thirteen participants in the mother condition made references to the self in their descriptions, and were therefore omitted. The remaining seven participants in the mother condition were used for the main analyses, and subsequently projected for further analyses.
Main analyses
To find out whether the three conditions significantly differed in terms of learning enjoyment, a one-way ANOVA was conducted to compare the effect of personal relevance on learning enjoyment in self, mother and halimah conditions. There was a significant main effect of personal relevance on learning enjoyment for the three conditions, F(2, 47) = 5.745, p = .006, ?2 = .196. A post hoc Tukey test showed that participants in the self (M = 4.095, SD = .567) and halimah (M = 3.52, SD = .569) conditions significantly differed in LE scores at p=.006. Participants in the self condition reported significantly higher learning enjoyment than halimah condition. However, the LE scores in the mother condition (M=3.562, SD=.651) did not significantly differ from self and halimah conditions at p=.100 and p=.569 respectively.
Next, a second ANOVA was conducted to investigate if personal relevance scores significantly differed across the three conditions. Main effect of condition on personal relevance emerged F(2, 47) = 4.009, p = .025, indicating significant differences in personal relevance across the three conditions. A post hoc Tukey test was conducted, and revealed that participants in the self (M = 3.952, SD = .628) and mother (M = 3.31, SD = .402) conditions significantly differed at p=.038, with PR scores being higher in the self condition compared to mother condition. However, the PR scores in Halimah condition (M=3.58, SD=.577) did not significantly differ from self and mother conditions, at p=.104 and p=.527 respectively.
Additionally, a third ANOVA was conducted to ascertain if IOS scores significantly differed across the non self conditions. The self condition was excluded since it was theoretically impossible to measure the extent one relates to themselves. Main effect of condition on IOS was found F(1, 27) = 49.794, p = .000, ?2 = .648 between the mother and halimah conditions, with IOS scores in the mother condition (M = 4.57, SD =1.51) being significantly higher than the halimah condition (M = 1.64, SD=.727).
Following this analysis, a final ANOVA was conducted to measure the effect of condition on performance change. Participants who scored >0 on their pre-tests were identified to be the group with prior knowledge, and participants who scored 0 for their pre-tests were the group with no prior knowledge. Overall, there were no significant effects of condition on performance change for participants (1) with and without prior knowledge F(2, 47) = 1.719, p=.190, (2) without prior knowledge only (pre-test scores = 0), F (2, 31)= 1.088, p=.349 and those (3) with prior knowledge only (pre-test scores >0), F (2, 13) =1.009, p=.391. In deciding whether to control for prior knowledge in an ANCOVA, Pearson’s correlation test was first conducted, and found no significant correlation between pre-test scores and performance change, r(48)= -.18, p=.21, hence there was no need to control for prior knowledge.
To determine the strength and directionality among variables of interest, Pearson’s correlation test was administered. Correlation results revealed a (1) non-significant correlation between PR and IOS, r(27)= .138, p=.477, a (2) significant correlation between PR and LE, r(48), .344, p=.014, and a (3) non-significant correlation between IOS and LE, r(27)=.145, p=.454.
The non-significant correlation between PR and IOS was an unexpected finding which prompted further investigation. PR and IOS were initially conceptualised as interrelated constructs, with IOS as a manipulation for PR. The lack of correlation between these two suggested possible confounding effects of a third variable, utility value (UV). UV is defined as the usefulness and perceived importance of a task (Wigfield & Eccles, 2000). Based on this definition, UV is more closely related to the PR aspect which emphasizes on application and utility, rather than the IOS aspect which focuses on closeness within interpersonal relationships.
Further Analyses
To find out if UV was confounding the relationship between PR and IOS, utility frequency in participants’ responses were coded as an additional variable. Two raters examined participants’ description of brain part usage, and counted the number of UVs present in each response. For instance, if a participant implied UV in their response e.g. “My cerebellum helps me maintain balance on a bike”, they were counted as one UV point. Using a dichotomized approach, utility frequency for all three conditions were manually computed. Inter-rater reliability was found to be moderate ICC (2, 1) = .767, indicating homogeneity across utility frequency scores.
As mentioned, PR and IOS may be conceptually different constructs on the basis of UV, although they were initially hypothesized to be the same. Since the concept of PR may comprise of UV elements, it was unknown if LE was caused by PR or UV per se. Hence, Pearson’s correlation tests were conducted to observe if there was a correlation between UV and LE and UV and PR. Results revealed no significant correlation between UV and LE, r(48) = -.001, p=.994 and between UV and PR, r(48)=.118, p=.414, suggesting that UV was not a cause for concern as a confounding variable, and therefore did not warrant further analysis.
While existing results demonstrate promising trends, LE still did not significantly differ between the self and mother conditions. This was not surprising as there were only seven data remaining in the mother condition, hence, the effect of “mother” was not salient enough. To equalize the number of participants in the mother condition with self and halimah, the same analyses were re-run, with data cloning of mother condition. Prior knowledge was also entered as covariate and controlled for in ANCOVA. Please refer to the endnotes section for statistical results of the first and final data projections.
Discussion
This study examined the effects of personal relevance on learning enjoyment. According to the final projected data, different degrees of PR indeed affects LE as there were distinct differences in LE between self vs mother and self vs halimah conditions. Participants also perceived mothers to be significantly closer to their selves compared to halimah, signalling the successful manipulation of personal relevance within non self conditions. Moreover, PR and IOS were negative correlated, suggesting that the two constructs are indeed related. A negative correlation was expected because when IOS scores increase, the individual feels closer to others (i.e. mother/halimah), resulting in lower personal relevance as they deviate from the self. Together, these results support the proposed hypothesis and expands current literature as the effects of personal relevance on learning enjoyment are applicable, even within the context of learning complex terminology like brain anatomy.
However, there were some non-significant effects which are worth delving deeper into. Despite repeated cloning, learning enjoyment between mother vs halimah conditions did not significantly differ in the final data projection. This could be attributed to novelty effects elicited in the halimah condition. Novelty effects refer to heightened responses towards new, unfamiliar stimuli (Poppenk, Kohler ; Moscovitch, 2010). Halimah’s celebrity status could have been interpreted as a novel experience by participants because common folks rarely associate themselves with high ranking politicians like the President. In our study, participants in the halimah condition also possessed very little knowledge of halimah’s life, as they gave stereotypical descriptions of what a president does, such as “shaking hands, waving to people or indicated that they did not know anything about halimah.”
Essentially, Bunzeck ; Duzel (2006) observed the effects of viewing novel vs familiar images on people’s brains through fMRI scans. They found that novel images stimulated dopamine pathways that were similarly triggered in response to rewards. This shows that, novelty in itself is cognitively perceived as a reward, and is therefore a likely explanation for increase in learning enjoyment. Simultaneously, unfamiliarity and curiosity were also found to pique learners’ interests, as they devoted more energy towards material that were new to them (Kidd ; Hayden, 2015). As such, the nonsignificant results between mother and halimah condition could be confounded by the novelty effects found in the halimah condition.
Furthermore, novelty effects could also account for the non-significant differences in performance change between self and halimah conditions. Performance change in halimah condition was surprisingly similar to the self condition although halimah was perceived to be distant from the self. Novelty may have memory-boosting effects from dopamine. Takeuchi et al (2016) found that novel experiences enhanced memory retention in mice. In a familiar setup, mice were trained to find food blocks and were able to remember the food location after an hour, but not after 24 hours. However, when presented with an unfamiliar floor surface, the mice remembered the food location even after 24 hours. In a similar way, encountering a novel subject like halimah may have boosted participants’ memory of brain parts and functions, resulting in a non-significant difference in performance change between self and halimah.
Additionally, while PR scores in Halimah condition and mother condition were not statistically significant, an examination of the means of the PR scores between the two conditions reveal contradictory findings. Higher PR scores was found in the halimah condition as compared to the mother condition. A possible explanation for this finding could be the situational context where this experiment took place. Recently, a controversy has sparked about Halimah’s presidential election. Since she was elected through a walkover (StraitsTimes, 2017), the public has has expressed mixed feelings and even outrage about it. News articles and videos of halimah were widespread across social media as netizens voiced their opinions and debated about this issue. As such, similar feelings could be invoked among our participants in the experiment. The salience of this political news may result in participants holding strong personal views about Halimah, making her more personally relevant at the current time as compared to mother who is a common household figure.
Educational implications
From these results, the impact of personal relevance on learning enjoyment is apparent. Educators should incorporate relevant components in classroom settings to stimulate positivity and enjoyment towards learning. Relevance can be integrated with cognitive strategies like retrieval practice and concept-mapping (Roediger ; Butler, 2010; Blunt ; Karpicke, 2014). Without relevance, these strategies merely repeat the information from textbooks. In concept-mapping for instance, learners can map additional branches that draw links to the self, for e.g. Amygdala emotions fear I fear cockroaches. This keeps the function of an amygdala salient in their mind as they subconsciously remember what they fear.
In addition, educators should embrace innovation and creativity as they are fundamental aspects of learning enjoyment. In Singapore’s context, students have to sit for school-based science practical assessments (SPA) where they conduct experiments based on the same set of instructions (SEAB, 2018). This standardized style of assessment suppresses creativity in a versatile subject like Science. It also does not evoke curiosity as students are assessed based on how well they execute those instructions. Some students may already have an innate interest in science, but their learning enjoyment is hindered by rigid examination formats. Hence, educators may consider allowing students to devise their own experiments with guidance and mentorship from their teachers. This way, they perceive personal relevance in pursuing an experiment of their interests, and engage with novel learning as it is something new and unfamiliar.
In the same vein, educators should also reframe the way they perceive education. The overemphasis on grades (Teng, 2016) hinders the potential of learning beyond examinations. It is difficult to contextualize textbook content to real life, if students are struggling to complete the syllabus or rush through assignments. Thus, most students resort to rote memorization which is effective in the short run, but does little to increase learning enjoyment or improve the learner’s competency in the subject. Hence, schools should reorganize academic schedules such that it allows time for students to internalize and apply content to relevant aspects of their lives.
Critically, learning should also be extended beyond the classroom (MacQuarrie, 2018) to help students relate their learning to the surrounding environment. For instance, in child abnormal psychology, students learn about the symptoms of various disorders and developmental stages, but these are merely theoretical and are hard to relate to if students have never interacted with special needs children. From this view, educators should increase the frequency of outdoor learning (e.g. child clinics) to help students perceive the relevance of their knowledge to the community, and even to the self, if it inspires students to pursue a career in child psychology.
Limitations and Future Directions
One limitation in the present research lies in the nature of the study. As a one-off event, it may be inadequate in capturing the effects of learning enjoyment, which occurs over a period of time (Daily, 1997). Since participants had no psychology background, the short duration may be insufficient for them to experience learning enjoyment. Future research may conduct longitudinal studies to examine learning enjoyment and subsequent academic outcomes over prolonged periods of time.
Perhaps, future studies should also include questionnaires that measure how personally relevant individuals feel towards different versions of their selves, and how that relates to perceived relevance in learning. An issue of concern pertains to whether the “self” truly reflects one’s core identity. Self consists of several subcomponents, such as the relational self, personal self, interpersonal self and ideal self. Individuals may feel closer to their relational self as compared to their ideal self. By using a broad definition of “self”, our study assumes “self” to be of highest personal relevance, as there was no way of measuring it through IOS scale. However, personal relevance may not necessarily imply self-relevance to one’s identity (Abraham, 2013). For example, a person’s favourite outfit may be personally relevant to them, but is not a central aspect of who they are. Some individuals may not even feel close to themselves, because they dislike the person they are, or lack self-confidence. Hence, further insights could be attained if different aspects of the self are analysed more closely.
Furthermore, earlier speculation identified novelty as a possible confound between personal relevance and learning enjoyment. The novelty encoding hypothesis suggests the usefulness of novelty in visual memory, as novel stimuli are more easily recognized than familiar stimuli. However, the exact relationship between novelty and enjoyment has not been established yet (Kormi-nouri, Nilsson & Ohta, 2005). Hence, future studies can take this further by investigating novelty effects on learning enjoyment.
Conclusion
In all, learning enjoyment is a crucial, yet undermined aspect of education. While most institutions acknowledge the benefits of enjoyment, it has not been sufficiently promoted in schools. Therefore, the present study illuminates the use of personal relevance as a promising strategy in driving learning enjoyment.
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Endnotes (1)
First data projection (N=64)
Projected main analyses
To find out whether the three conditions significantly differed in terms of learning enjoyment, a one-way ANOVA was conducted to compare the effect of personal relevance on learning enjoyment in self, mother and halimah conditions. According to projected data, there was a significant main effect of personal relevance on learning enjoyment for the three conditions, F(2, 61) = 6.327, p = .004, ?2 = .172. A post hoc Tukey test showed that participants in the self (M = 4.10, SD = .570) and mother (M = 3.56, SD = .617) conditions significantly differed in LE scores at p=.012. Participants in the self (M = 4.10, SD = .570) and halimah (M = 3.52, SD = .569) conditions also significantly differed in LE scores at p=.006. However, the LE scores in the mother condition (M = 3.56, SD = .617) did not significantly differ from the halimah conditions (M = 3.52, SD = .569) at p=.974.
Next, a second round of one-way ANOVA was conducted to investigate if personal relevance scores significantly differed across the three conditions. Main effect of condition on personal relevance emerged F(2, 61) = 7.497, p = .001, indicating significant differences in personal relevance scores among the three conditions. A post hoc Tukey test was conducted, and revealed that participants in the self (M = 3.95, SD = .628) and mother (M = 3.31, SD = .083) conditions significantly differed at p=.001, with PR scores being higher in the self condition compared to mother condition. PR scores between the self (M = 3.95, SD = .628) and halimah (M = 3.58, SD = .577) conditions were also marginally significant at p=.072. However, the PR scores in halimah condition (M=3.58, SD=.577) did not significantly differ from the mother condition, at p=.228.
Also, another round of one-way ANOVA was conducted to ascertain if IOS scores significantly differed across the non self conditions. The self condition was excluded since it was theoretically impossible to measure the extent one relates to themselves. Main effect of condition on IOS was found F(1, 41) = 72.651, p = .000, ?2 = .639 between the mother and halimah conditions, with IOS scores in the mother condition (M = 4.57, SD =1.51) being significantly higher than the halimah condition (M = 1.64, SD=.727).
Following this analysis, a final one-way ANOVA was conducted to measure the effect of condition on performance change. There was a significant main effect of condition on performance change F(2, 61) = 4.204, p = .019, among participants with and without prior knowledge. Within this sample, a post hoc Tukey test found that self (M = 3.38, SD=2.06).
and mother (M = 2.00, SD=1.73) conditions significantly differed in performance change at p = .047. Mother (M = 2.00, SD=1.73) and halimah (M = 3.45, SD=1.71) conditions also displayed significant differences in performance change at p = .032. However, there was no significant difference in performance change between self (M = 3.38, SD=2.06) and halimah (M = 3.45, SD=1.71) conditions, at p=.991.
For participants with no prior knowledge (pre-test scores =0), the main effect of condition on performance change was not significant, F(2, 41) = 2.677, p = .081. For those with prior knowledge (pre-test > 0), the main effect of condition on performance change was also not significant, F(2, 17) = 2.17, p = .144. In deciding whether to control for prior knowledge in an ANCOVA, Pearson’s correlation test was first conducted, and found no significant correlation between pre-test scores and performance change, r(62)= -.16, p=.22, hence there was no need to control for prior knowledge.
To determine the strength and directionality among variables of interest, Pearson’s correlation test was administered. Correlation results revealed a (1) significant correlation between PR and IOS, r(41)= -.310, p=.477, a (2) significant correlation between PR and LE, r(60), .278, p=.026, and a (3) non-significant correlation between IOS and LE, r(41)=.196, p=.207.
Endnotes (2)
Final data projection (N=128)
Final projected main analyses
To find out whether the three conditions significantly differed in terms of learning enjoyment, a one-way ANOVA was conducted to compare the effect of personal relevance on learning enjoyment in self, mother and halimah conditions. There was a significant main effect of personal relevance on learning enjoyment for the three conditions, F(2, 125) = 12.955, p = .000, ?2 = .172. A post hoc Tukey test showed that participants in the self (M = 4.10, SD = .563) and mother (M = 3.56, SD = .610) conditions significantly differed in LE scores at p=.000. Participants in the self (M = 4.10, SD = .563) and halimah (M = 3.52, SD = .562) conditions also significantly differed in LE scores at p=.000. However, the LE scores in the mother condition (M = 3.56, SD = .610 ) did not significantly differ from the halimah conditions (M = 3.52, SD = .562) at p=.947.
Next, a second round of one-way ANOVA was conducted to investigate if personal relevance scores significantly differed across the three conditions. Main effect of condition on personal relevance emerged F(2, 125) = 15.362, p = .001, indicating significant differences in personal relevance scores among the three conditions. A post hoc Tukey test was conducted, and revealed that participants in the self (M = 3.95, SD = .621) and mother (M = 3.31, SD = .376) conditions significantly differed at p=.000, with PR scores being higher in the self condition compared to mother condition. PR scores between the self (M = 3.95, SD = .621) and halimah (M = 3.58, SD = .570) conditions were also significant at p=.005. Lastly, the PR scores in halimah condition (M=3.58, SD=.570) significantly differend from the mother (M = 3.31, SD = .376) condition at p=.049.
Also, another round of one-way ANOVA was conducted to ascertain if IOS scores significantly differed across the non self conditions. The self condition was excluded since it was theoretically impossible to measure the extent one relates to themselves. Main effect of condition on IOS was found F(1, 84) = 148.846, p = .000, ?2 = .639 between the mother and halimah conditions, with IOS scores in the mother condition (M = 4.57, SD =1.42) being significantly higher than the halimah condition (M = 1.64, SD=.72).
Following this analysis, a final one-way ANOVA was conducted to measure the effect of condition on performance change. There was a significant main effect of condition on performance change F(2, 125) = 8.615, p = .000, among participants with and without prior knowledge. Within this sample, a post hoc Tukey test found that self (M = 3.38, SD=2.03) and mother (M = 2.00, SD=1.71) conditions significantly differed in performance change at p = .002. Mother (M = 2.00, SD=1.71) and halimah (M = 3.45, SD=1.69) conditions also displayed significant differences in performance change at p = .001. However, there was no significant difference in performance change between self (M = 3.38, SD=2.03) and halimah (M = 3.45, SD=1.69) conditions, at p=.981.
For those without prior knowledge (pre-test=0), a significant main effect of condition on performance change emerged, F(2, 85) = 5.550, p = .005, ?2 = .116. A post hoc Tukey test revealed significant differences in performance change between self(M = 3.77, SD=2.27)
and mother (M = 2.2, SD=1.87) conditions at p = .010 and between mother (M = 2.2, SD=1.87) and halimah (M = 3.56, SD=1.87) conditions at p = .020. However, there were no significant differences in performance change between self M = 3.77, SD=2.27) and halimah (M = 3.56, SD=1.87) conditions at p =.916. For those with prior knowledge (pre-test >0), a significant main effect of condition on performance change emerged, F(2, 37) = 4.733, p = .015. A post hoc Tukey test revealed significant differences in performance change between the self (M = 32.75 SD=1.44) and mother (M = 1.50, SD=1.57) conditions at p = .061 and between mother and halimah (M = 3.17, SD=1.11) conditions at p = .015. However, no significant differences were found between self (M = 32.75 SD=1.44) and halimah (M = 3.17, SD=1.11) conditions at p =.715.
Since performance change significantly varied across the groups, prior knowledge was entered as a covariate, to find out if the same pattern was produced, even when controlling for prior knowledge. An ANCOVA conducted revealed a significant effect of condition on performance change, controlling for prior knowledge, F(2, 124) = 8.710, p = .000, ?2p = .116. A post hoc Tukey test revealed significant differences in performance change between self (M = 3.38 SD=2.04) and mother (M = 2.00, SD=1.71) conditions at p = .000 and between mother (M = 2.00, SD=1.71) and halimah (M = 3.45, SD=1.69) conditions at p = .000 However, there were no significant differences in performance change between self (M = 3.38 SD = 2.04) and halimah (M = 3.45, SD=1.69) conditions at p =.950. This shows that performance change varies as a result of personal relevance, even after controlling for prior knowledge. Since the trend is the same as before, prior knowledge does not significantly affect the performance of the three conditions.
To determine the strength and directionality among variables of interest, Pearson’s correlation test was administered. Correlation results revealed a (1) significant correlation between PR and IOS, r(84)= -.310, p=.004, a (2) significant correlation between PR and LE, r(126), .278, p=.001, and a (3) marginally significant correlation between IOS and LE, r(84)=.196, p=.070.
Comparison of M and SD across different data sets
Table 1: Descriptive statistics for main effect of condition on LE across actual data, first projected data and final projected data
Actual Data 2nd projected data Final projected data
M SD M SD M SD
Self 4.095 .567 4.10 .570 4.10 .563
Mother 3.562 .651 3.56 .617 3.56 .610
Halimah 3.52 .569 3.52 .569 3.52 .562
Table 2: Descriptive statistics for main effect of condition on PR across actual data, first projected data and final projected data
Actual Data 2nd projected data Final projected data
M SD M SD M SD
Self 3.952 .628 3.95 .628 3.95 .621
Mother 3.31 .402 3.31 .083 3.31 .376
Halimah 3.58 .577 3.58 .577 3.58 .570
Table 3: Descriptive statistics for main effect of condition on IOS across actual data, first projected data and final projected data
Actual Data 2nd projected data Final projected data
M SD M SD M SD
Mother 4.57 1.51 4.57 1.51 4.57 1.42
Halimah 1.64 .727 1.64 .727 1.64 .72
Appendix A
Pre-intervention test
Which of the following brain parts do you know the function of ? (Check all that applies)
Cerebellum
Thalamus
Hippocampus
Amygdala
Nucleus Accumbens
None of the above
(Subsequent questions displayed depends on brain parts that were checked )
8219322748700What are the functions of the cerebellum?
What are the functions of the thalamus?
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What are the functions of the hippocampus?
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What are the functions of the amygdala?
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What are the functions of the nucleus accumbens?
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Appendix B
Intervention
Study the following diagram and answer the question below. You have 5 minutes to do so. (“Click to proceed” button will appear after a while)
Cerebellum
Write down one experience where you/your mother/ President Halimah (according to allocated condition) would have previously used her cerebellum. Describe the function and implications of the cerebellum during this specific incident.
Thalamus
Write down one experience where you/your mother/ President Halimah (according to allocated condition) would have previously used her Thalamus. Describe the function and implications of the Thalamus during this specific incident.
Hippocampus
Write down one experience where you/your mother/ President Halimah (according to allocated condition) would have previously used her Hippocampus. Describe the function and implications of the Hippocampus during this specific incident.
Amygdala
Write down one experience where you/your mother/ President Halimah (according to allocated condition) would have previously used her Amygdala. Describe the function and implications of the Amygdala during this specific incident.
Nucleus Accumbens
Write down one experience where you/your mother/ President Halimah (according to allocated condition) would have previously used her Nucleus Accumbens. Describe the function and implications of the Nucleus Accumbens during this specific incident.
Appendix C
Personal Relevance (PR) Scale
Please read each of these statements and indicate the extent to which you relate to them while going through the slides.
Strongly Disagree Somewhat Disagree Neither Agree nor Disagree Somewhat Agree Strongly Agree
After reading the slides, I learnt about the world outside of school. New learning starts with problems about the world outside of school. I learnt how biological psychology can be part of my out-of-school life. I gained a better understanding of the world outside of school. I learnt interesting things about the world outside of school. What I learnt has nothing to do with my out-of-school life. Appendix D
Learning Enjoyment (LE) Scale
Please read each of these statements and indicate the extent to which you agree or disagree with them.
Strongly Disagree Somewhat Disagree Neither Agree nor Disagree Somewhat Agree Strongly Agree
I look forward to studying about the human brain. I enjoy the challenge of learning the material. I enjoy acquiring new knowledge about the human brain. I enjoy dealing with the course material on the topic of the human brain Reflecting on my progress in coursework makes me happy. I study more than required because I enjoy it so much. I am so happy about the progress I made that I am motivated to continue studying. Certain subjects are so enjoyable that I am motivated to do extra readings about them. When my studies are going well, it gives me a rush. I get physically excited when my studies are going well. Appendix E
Inclusion of Self and Others (IOS) Scale
Which diagram best represents how close you feel to your mother/President Halimah ? (depending on assigned condition)
1 – Not close at all
7 – Extremely close
Appendix F
Post-intervention test
What are the functions of the Thalamus?
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What are the functions of the Cerebellum?
0-63500
What are the functions of the Nucleus accumbens?
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What are the functions of the Amygdala?
0-63500
What are the functions of the Hippocampus?
0000
Appendix G
Scoring rubric for pre and post intervention tests
Brain part Answer/ Key words Other possible variations Marks
Cerebellum Coordinating movement Muscle coordination 1
Maintaining balance Keeping us upright 1
Thalamus Relay information Sending information 1
Sensory information Send information to senses 1
Hippocampus Memory/ Long term memory – 1
Forming new memories Creating new memories 1
Amygdala Perceiving emotions Understanding emotions 1
Memory of events that accompanied emotions Remembering emotionally charged events 1
Nucleus Accumbens Reward/ pleasure Joy 1
Addiction/ impulsivity – 1
Appendix H
Hypothesis Check
034692400What is your age?
What is your gender?
Male
Female
What is your race?
Chinese
Malay
Indian
Other
034829400Where are you currently studying?
What is your major of study?
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What do you think is the hypothesis of our study?
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