Mood states, self-set goals, self-efficacy and performance in academic examinations

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<ul><li><p>The present study investigated relationships between mood, performance goals, and both written and</p><p>* Corresponding author. Tel.: +44 23 92 845164.E-mail address: richard.thelwell@port.ac.uk (R.C. Thelwell).</p><p>www.elsevier.com/locate/paid</p><p>Personality and Individual Dierences 42 (2007) 5735830191-8869/$ - see front matter 2006 Elsevier Ltd. All rights reserved.oral examination performance. Fifty-seven undergraduate students completed a mood measure thatassessed the subscales of anger, calmness, confusion, depression, fatigue, happiness, tension and vigor, indi-cated the grade set as a goal for the examinations, and rated their condence to achieve this goal. Thesemeasures were completed approximately 30 min before each examination. Structural equation modellingresults indicated that mood states, self-ecacy and self-set goals predicted 20% of oral examination perfor-mance and 7% of written examination performance. In both samples, ndings indicate that positive moodstates are associated with self-ecacy to achieve self-set goals. We suggest that future research should lookat the extent to which intervention strategies designed to enhance mood states are associated with enhancedperformance. 2006 Elsevier Ltd. All rights reserved.</p><p>Keywords: Emotion; Performance; Self-ecacy; Cognition; Applied psychologyMood states, self-set goals, self-ecacy and performancein academic examinations</p><p>Richard C. Thelwell a,*, Andrew M. Lane b, Neil J.V. Weston a</p><p>a Department of Sport and Exercise Science, University of Portsmouth, Spinnaker Building,</p><p>Cambridge Road, Portsmouth PO1 2ER, UKb School of Sport, Performing Arts and Leisure, University of Wolverhampton,</p><p>Gorway Road, Walsall WS1 3BD, UK</p><p>Received 7 October 2005; received in revised form 5 July 2006; accepted 26 July 2006Available online 5 October 2006</p><p>Abstractdoi:10.1016/j.paid.2006.07.024</p></li><li><p>574 R.C. Thelwell et al. / Personality and Individual Dierences 42 (2007) 5735831. Introduction</p><p>There has been an increase in the amount of empirical research suggesting psychological statessuch as mood to be predictive of performance, especially in situations that have a high degree ofpersonal importance. Dened as a set of feelings, ephemeral in nature, varying in intensity andduration, and usually involving more than one emotion (Lane &amp; Terry, 2000, p. 16), mood hasbeen reported to inuence individuals in a number of situations that have included athletic com-petition (Beedie, Terry, &amp; Lane, 2000) and academic examinations (Catanzaro, 1996; Lane,Whyte, Terry, &amp; Nevill, 2005; Totterdell &amp; Leach, 2001). A theoretical position forwarded to ex-plain such eects is the notion that the moods experienced by the individual serve in an informa-tional manner. Thus the mood as information hypothesis suggests that the aective content ofmood states provide information on personal resources to cope with task demands, and it is be-lieved that the predictive eects of mood states are especially salient when the outcome of theactivity is uncertain (Bless, 2001; Gendolla &amp; Krusken, 2002). With this in mind, it is likely thatnegative or unpleasant moods will associate with a dicult or problematic situation, where infor-mation regarding the self, task and coping strategies are negatively phrased. Should this occur, itis also likely that the negative moods will relate to low self-ecacy (Bandura, 1990). In contrast,positive moods are more likely to provide functional information for the individual regarding thesituation, and relate to high self-ecacy.Acknowledging how situations often inuence mood states held by the individual, it is impor-</p><p>tant to be aware that when the situation is one of importance, mood states may inuence perfor-mance in both a positive or negative manner. Whilst individuals may wish to experience positivemoods prior to a dicult or uncertain event, it is often the case that individuals will experiencenegative moods due to the discrepancy between the demands of the task and the resources thatthe individual has at their disposal to cope with the situation (Carver &amp; Scheier, 1990; Martin&amp; Tesser, 1996). As a result, individuals who experience negative moods may attend to specicinformation in greater detail to reduce the discrepancy that may be present for the task (Cervone,Kopp, Schaumann, &amp; Scott, 1994). If that is the case then it may be the goals set within the taskthat are more appropriate to examine, rather than global performance. For example, in an exam-ination, a student may have a very negative mood due to perceiving the task demands to outweightheir personal resources needed to achieve a high grade. As a result, they may use the negativemood state to help them mobilize their eort in a functional manner towards the goal of achievinga threshold pass. Alternatively, the negative mood may act in a dysfunctional manner and disableany mobilization of eort due to the attainability of the goal (task demands) being too high (Gen-dolla &amp; Krusken, 2002). Thus, as argued by Bandura (1990), individuals with low self-ecacyexpectations before doing a personally important task could result in experiencing feelings ofdespondency, especially if they anticipate failure.Taking the theoretical suggestions for the relationships between mood states, self-ecacy and</p><p>performance forward, recent research (e.g., Lane et al., 2005) has found that pre-examinationmood states are not only predictive of performance, but are also related to the diculty ofself-set goals, and self-ecacy estimates to achieve these goals. Specically, Lane et al. reportedsignicant positive intercorrelations between vigor, self-ecacy, self-set goals and examinationperformance among a sample of 50 undergraduate students for a practical examination. Whilst</p><p>an insight to the potential inuence of depressed mood on mood states, goals, and performance</p></li><li><p>within an academic context was provided, Lane et al. indicated that before the ndings could be</p><p>R.C. Thelwell et al. / Personality and Individual Dierences 42 (2007) 573583 575used in applied settings, replication was needed. They also commented that future research shouldseek to explore the predictive eectiveness of mood on dierent forms of assessment, given thattheir ndings were limited to practical forms of summative assessment. To develop the knowledgeand understanding to this area of research, it is therefore appropriate to gain a more detailedunderstanding to whether similar ndings are evident within alternative forms of summativeassessment.The aim of the present study is to further the research by Lane et al. (2005) to incorporate alter-</p><p>native forms of academic assessment. The two forms of assessment included (a) the traditionalwritten examination, and, (b) the contemporary oral (viva-style) examination. For both formsof examination, the purpose was to examine relationships between pre-examination mood states,goals, self-ecacy, and actual examination performance. The present study tested the notion thatmood states predicted cognitive states (goals and self-ecacy) and that mood states and cognitivestates predict performance. The hypothesized model is depicted in Fig. 1. It should be noted thatFig. 1 represents the starting point to developing a theoretical framework. The present studysought to operationalize mood, using subcomponents of the construct, thereby assess specicaective states such as anger, depression, etc., rather than a single measure of mood that com-bined specic states under a general heading. This approach to assessing mood is consistent withthe notion that the aective content of mood provides information and it is this information thatinuences performance.Mood states Goals</p><p>Self-efficacy</p><p>Performance</p><p>Fig. 1. Hypothesized model for relationships between mood states, self-set goals, self-ecacy and performance.2. Methods</p><p>2.1. Participants</p><p>Volunteer participants were 57 (Male n = 32, Female n = 25: Age range 1828 years) under-graduate students studying for a degree in Sports Science at the University of the rst author.</p><p>2.2. Measures</p><p>Mood was measured using the Brunel Mood Scale-32 (BRUMS-32) that has been recentlydeveloped (see Lane &amp; Jarrett, 2005) from two previously validated scales (Matthews, Jones, &amp;</p></li><li><p>576 R.C. Thelwell et al. / Personality and Individual Dierences 42 (2007) 573583Chamberlain, 1990; Terry, Lane, Lane, &amp; Keohane, 1999; Terry, Lane, &amp; Fogarty, 2003). The ori-ginal Brunel Mood Scale (BRUMS: Terry et al., 1999, 2003) is a 24-item mood state scale basedon the Prole of Mood States (McNair, Lorr, &amp; Droppleman, 1971). The BRUMS assesses themood states of anger, confusion, depression, fatigue, tension, and vigor. The current 32-item scalewas formed by adding the items that assess the subscales of happiness and calmness from theUWIST (Matthews et al., 1990) to the 24-items from the BRUMS. The argument for includinga greater number of positive mood states was in response to the frequently cited limitation thatthe POMS has an excessively negative orientation. To this end, it has been suggested in recent lit-erature (e.g., Hanin, 2000) that positive mood dimensions, such as happiness and calmness, mayalso inuence performance. With the addition of the two new subscales, the BRUMS-32 is sug-gested to provide a more balanced assessment of positive mood and negative mood, and it hasalso been employed in recent mood-related research (e.g., Thelwell, Weston, Lane, &amp; Greenlees,2006).Each of the eight subscales within the BRUMS-32 has four items. Examples of Anger items in-</p><p>clude Annoyed and Bitter, Confusion items include Muddled and Confused, Depressionitems include Miserable and Unhappy, Fatigue items include Exhausted and Sleepy,Tension items include Nervous and Worried, and Vigor items include Active and Lively.Calmness items include Restful and Composed and Happiness items include Contentedand Satised. All items within the BRUMS-32 are rated on a 5-point scale where a responseof 0 equals not at all and 4 equals extremely. Alpha coecients for each subscale in the presentstudy were over .70.</p><p>2.3. Academic goals and goal-condence</p><p>Prior to each of the examinations, participants were asked to indicate the grade that they set asa goal for the examination. They were also asked to rate the condence that they have for achieve-ment of the goal. Goal-condence was rated on a 9-point scale where 1 = no condence at all,and 9 = very condent.</p><p>2.4. Examination performance</p><p>The two methods for assessing examination performance included traditional written examina-tion performance and a more contemporary oral examination. The written examination (Intro-duction to Sport and Exercise Psychology) was 1.5 h in length and comprised two sections wheresection one had 45 multiple-choice questions (not negatively marked) that had to be answered.Section two had a total of 5 essay titles where students were required to answer 1. The overallgrade for the examination took into account performance in both sections. In accord with theUniversitys assessment policy, on completion of the examination, all students work was markedand a total of 10% of the examination scripts were subjected to blind second marking by a subjectspecialist. All double marked work was then stored and made available for the Subject ExternalExaminer to ensure that the assessment policy had been adhered to, and that appropriate markshad been awarded.The oral assessment (Introduction to Sports Physiology) was a new form of assessment with-in the curriculum (see Oakley, 2004 for a full review). Each student was required to answer a total</p></li><li><p>R.C. Thelwell et al. / Personality and Individual Dierences 42 (2007) 573583 577of six questions within their oral examination, where a total of three learning outcomes (two ques-tions per learning outcome) were assessed. To enable variety in the questions posed, the unit coor-dinator was required to prepare a question-bank of 1020 questions for each learning outcome. Apro-forma marking sheet was used to grade student responses to each question on a 05 scale,using set marking criteria that enabled an overall mark to be given.Although two members of sta examined the students in the oral assessment (thus providing</p><p>double marking), having gained consent from the students, some of the oral assessments were taperecorded to enable commentary from the Subject External Examiner to ensure that the assessmentpolicy had been adhered to and that students were awarded appropriate grades. For both forms ofassessment, conrmed student grades were made available following the Examination Board. Themarking system employed ranges from 0% to 100% where marks of 70% + equated to a rst classpass, marks between 60% and 69% equated to an upper second class pass, marks between 50% and59% equated to a lower second class pass, marks between 40% and 49% equated to a third classpass, and, marks of 39% or below equated to a fail.</p><p>2.5. Experimental procedures</p><p>Prior to the study commencing, participants completed written informed consent forms havingbeen provided with detailed participant information sheets outlining the nature and methodologyof the study. Having ensured condentiality, participants completed a BRUMS-32, and indicatedtheir percentage goal for the examination (0100) and condence in their ability to achieve thegoal (rated on a 9-point scale where 1 = no condence and 9 = very condent) approximately30 min prior to their written and oral examinations (that were over one week apart). Data werechecked for missing data before collecting. Participants were asked if missing data was intended oraccidental. Of the few cases of missing data, all were due to missing items and participants com-pleted the missing items. Also prior to the summative assessments, all students had completed for-mative assessments for each topic area. The study had ethical approval from the institution of therst author.</p><p>2.6. Data analysis</p><p>A repeated measures multivariate analysis of variance (MANOVA) was employed to examinethe dierences in pre-examination mood, the performance goal set pre-examination, the con-dence to achieve the performance goal, and, the actual examination performance before the writ-ten examination, and oral examination.Structural equation modelling (SEM) techniques were used to assess the strength and direction</p><p>of hypothesized relationships between mood states, cognitive states and performance in the twoexamination conditions. Multisample structural equation modelling was used to assess the extentto which relationships diered by examination type. Consistent with the data analysis strategy ap-proach used by Scott-Lennox and Scott-Lennox (1995), a fully recursive model with equality con-straints on all hypothesized relationships was used. Moderation is inferred when relationshipsdier between examination type. Structural equation modelling was used to analyse relationshipsbetween variables within the correlation matrix in each examination condition. Whilst it is possi-</p><p>ble to use a correlation matrix to examine the strength and direction of relationshi...</p></li></ul>