Links between affective and academic outcomes

attitudes and behaviourSummary

  •  This overview uses a mixture of existing evidence and a new search of electronic databases.
  • It considers the evidence that teachers can affect pupil affective characteristics and behaviour which in turn can affect school outcomes.
  • There is very little evidence relevant to enhancing post-school participation.
  • There is insufficient evidence that pupil aspirations and expectation can be used to improve attainment at school.
  • There is little evidence that pupil attitudes to education and motivation can be improved by teachers in order to improve attainment at school.
  • Mental characteristics such as self-esteem and locus of control are confusing in the literature. There is almost no evidence that they can be used to improve attainment at school.
  • There are teacher-led interventions that can improve pupil poor behaviour, and that are strongly associated with improved attainment. The sequence to attainment is not clear, but there is promise here.
  • A similar but weaker situation emerges for social and emotional competence and well-being. There are some teacher-led interventions that can improve pupil well-being and that are sometimes associated with improved attainment.
  • There have been no trials of teacher influence on civic participation to improve attainment. There is some promise here from the work that has been done on teacher influence (not from pedagogy but in personal interactions).
  • In conclusion, the most promising areas for teachers to pursue come within the domain of promoting pro-social pupil behaviour, including citizenship, and respect for and trust in others.
  • The appendix presents some ideas for assessing affective measures, and some of the clear difficulties in doing so validly.


We were asked to summarise existing evidence on the link from the kinds of pupil behaviours or affective characteristics that are susceptible to formation by interaction with teachers to attainment outcomes for potentially disadvantaged pupils. This is a complex causal model. It involves looking for actions, practices or interventions that can be conducted by teachers (A), that will have a differential impact on the attitudes and development of pupils from more disadvantaged backgrounds (B), and that will in turn have an impact on educational outcomes like attainment and subsequent participation (C). Related issues include the definition and successful identification of pupils from more disadvantaged backgrounds, and the definition and valid measurement of pupil development and attitudes. But the most difficult part is to find convincing evidence of the causal model itself. We need to establish a firm association between A and B and between B and C. We need to discount the otherwise important evidence of a direct link between A and C. We need to eliminate any evidence of the sequence from B to A, C to B or C to A. And then we either need to show that the ABC impact pathway is differentially important for more disadvantaged pupils, or that it could be implemented only for more disadvantaged pupils without ethical concerns. For each stage in the model, it is possible that we could find evidence to support it, evidence against it, or no clear evidence either way.


The research questions include:

  • Do affective characteristics such as ambition, well-being, sense of worth, resilience, communications and problem-solving help improve the academic outcomes of pupils from disadvantaged backgrounds?

If so,

  • Can these affective outcomes be measured by easy to administer questionnaire/surveys? Can teachers influence these affective characteristics?


In presenting this overview briefing paper, we draw on a number of pieces of existing research, and a bespoke review of the relevant literature conducted for Teach First. The existing research includes studies of measuring disadvantage (e.g. Gorard 2012), school intakes (e.g. Gorard and Cheng 2011), identifying the impact of schools and teachers (e.g. Gorard 2010), the determinants of wider outcomes of schooling (e.g. Gorard and See 2011), and the role of teachers in affective outcomes (Gorard and Smith 2010), plus reviews of participation in FE (e.g. See et al. 2011), HE (e.g. Gorard et al. 2007), and beyond (Selwyn et al. 2006), and of the causal link between pupil attitudes and subsequent attainment (Gorard et al. 2011). There is no space to reprise all of this primary and secondary evidence here, and readers will have to follow up via the references.   The bespoke review involved electronic search of education databases for work including terms such as:

Interpersonal skill
Democratic participation
Communication skills
Motivation to learn

Only work in the English language was sought, and after searching research was only excluded on the grounds of lack of relevance, method or comprehensibility.   In general, the evidence-base linking affective characteristics and post-compulsory education was weak, largely because the relevant work has not been conducted. Therefore, almost all that follows concerns attainment, rather than participation, as an outcome.

The wider picture

Any search for evidence that is inclusive enough to be anywhere near comprehensive will inevitably lead to research reports that are only tangentially related to the model above. We have largely ignored evidence on structural issues such as the funding model for schools, the quality and supply of teachers, the possible peer effect produced by the ways in which pupils are allocated to schools, and non-educational factors such as family influence, talent, levels of poverty and the intersections of indicators of possible disadvantage. All of these, and many others, are relevant to pupil attainment at school. However, they are not susceptible to formation through interaction with teachers.

There is a considerable body of evidence on generic teaching interventions to improve attainment that do not involve affective characteristics. There is a smaller though still considerable body of evidence on promoting improvements in pupil affective and mental characteristics, often via attainment and participation. In all of these the affective characteristic is not shown to lead to the attainment outcome.

For example, aspirations and expectations have been linked as outcomes in themselves to events in school (Feinstein et al 2004), a sense of achievement at school (Ahmavaara and Houston 2007), actual achievement at school (Trusty 2002, Wigfield et al. 2006), the practice of grade retention (Wiley 2006), interactions with teachers (Gorard 2011a), media portrayals of gender and racial stereotypes (Scott 2004), equivalent teacher or parent stereotypes (Tiedemann 2000), and the interplay of parent attitudes and structural features of the educational system such as whether there is selective secondary schooling (Buchmann and Dalton 2002). Motivation might be affected by instructional strategies (Frampton 2010), and some interventions are designed simply to teach motivation to students (Tuckman 2003). Anxiety about learning may be reduced by innovative approaches to teaching (Hong 2010). Ireland et al. (2006) found that Aimhigher activities, such as visits to higher education institutions, discussions with staff and current undergraduates in higher education, and participation in an Aimhigher Roadshow and week-long summer school, were associated with young people’s intentions and attitudes towards higher education. Abbey et al. (2000) described a family-based substance abuse prevention programme.

Further, the pupil characteristics and behaviours themselves may be inter-related, so that self-efficacy is claimed to promote higher aspirations (Bassi et al. 2007), or mediate the relationship between self-concept and achievement (Hejazi et al. 2009). Emotional competence predicts academic competence (Trentacosta and Izard 2007). Interest and self-efficacy are apparently mutually reinforcing (Tracey 2002). Kovach (2003) investigated the interactions between ethnic identification and self-esteem with regard to adolescent academic motivation and achievement. Results show that students who reported a strong ethnic identity were more motivated toward achieving academically than their peers. School engagement is apparently linked to parental support for schooling (Benner et al. 2008, Dearing et al. 2008), and child motivation to mother-child interaction (Vincson 2008). Gottfried et al. (2008) suggested that parental motivational practices are related to children’s academic intrinsic motivation from childhood through adolescence. Plunkett et al. (2009) found a modest relationship between a mother’s homework help and monitoring, and her child’s academic orientation. Perhaps most importantly for the rest of this review, falling short of one’s early expectations and aspirations might lead to lower emotional and psychological well-being in adulthood (Hardie 2010).

Instead, this briefing overview looks in turn at a range of possibly malleable pupil characteristics and whether changes in these can lead to improved attainment or participation.

Aspirations, expectations and intentions

Aspiration is what an individual hopes will happen in the future. This hope could be for happiness (NatCen 2005), attainment at school (Jacob and Wilder 2010), participation in education beyond school (Cuthbert and Hatch 2008), or occupational or financial success (Gorard and Smith 2010). Some studies use the term interchangeably with intention, and sometimes with expectation – or what an individual believeswill happen in the future. Most individuals have positive general aspirations, regardless of SES. There is some stratification, by area of residence (Lupton and Kintrea 2008, Carson 2009), concentrations of behavioural and mental disorders (David 2010), family SES (Geckova et al. 2010), parental education (Addington 2005, Schlechter and Milevsky 2010), and ethnicity (Guyll et al. 2010).

There is a link between aspirations/expectations and subsequent attainment (Desforges with Abouchaar 2003, Flouri 2006, Blaver 2010), but this could be partly the well-known link between SES and attainment in another form (Turok et al, 2008, McKendrick et al. 2007, Calder and Cope 2005, Marjoribanks 2005). The association could also be due to expectations created by levels of attainment, rather than the other way around. Some studies have found no contextualised association between aspirations and outcomes (Beal and Crockett 2010, Strand 2007). The sequence of events is not clear (Gutman and Akerman 2008, Strand and Winston 2008, Phillipson and Phillipson 2007, Gottfredson 2002, Bui 2007). And pupil intentions for education are less accurate as predictions than just guessing (in Croll 2009). Perhaps more importantly, there is little or no evidence that raising aspirations influences educational outcomes, partly because so little work has attempted to test it rigorously.

Therefore, there is evidence that teachers can assist in raising pupil aspirations, which are largely unstratified by SES, but no good evidence that this makes any difference to attainment or subsequent participation. There is some evidence that child aspirations are already realistic, and to increase them further might be more than the UK labour market and higher education system can cope with (St Clair and Benjamin 2011). We have reason to believe that teachers can generally improve educational outcomes for disadvantaged pupils through raising aspirations/expectations.

Motivation and attitude to education

Motivation is reason why an individual makes a decision, and their commitment to carrying that decision out. Some studies link it to attitude to education, such as an individual’s liking for school, or belief that school is important for their future.

A number of studies have suggested weak associations between reported learner motivation and attainment or retention (Singh et al. 2002, OECD 2003, Robbins et al. 2006, Unrau and Schlackman 2006, Van de gaer et al. 2007, Ream and Rumberger 2008, Quirk et al. 2009, Somers et al. 2009). Self-motivation or intrinsic motivation is linked to higher attainment (Hayenga and Corpus 2010, Cheng and Ickes 2009). The highest quality and largest study in this area found no evidence that reported intrinsic motivation was linked to later attainment (Keith and Cool 1992), confirmed by Zanobini and Usai (2002) and Dowson et al. (2003). If prior attainment and other context variables are included, then motivation is irrelevant to later attainment (Schwinger et al. 2009, Gagne and St Pere 2001). The evidence for a link between individual attitudes to education and outcomes is even weaker (Twist et al. 2007, Hillman 2010 Abu-Hilal 2000). And even this association seems to be the reverse of what is needed. Success or failure in education leads to the attitude more often than the other way around (Mattern and Schau 2002, Ma and Xu 2004, Hom 2004). In fact, success or failure at school can be a determinant of later participation in education (Gorard 2008).

Few controlled interventions have been conducted that show changing attitudes leading to better school outcomes. The studies that claim success are often the weakest. For example, Ben-Avie  and Steinfeld (2001) reported success for a three-year evaluation of the Institute for Student Achievement (ISA) programme for students at risk of failure or dropping out. Support was given to enhance motivation, personal accountability, parental involvement, and student relationship with school. The study involved only four schools, had no comparator for most outcomes, and the report does not even include the number of students involved. Using an approach like instrumental variables, claimed to mimic an experimental design, with a large dataset and contextual information, suggests that these correlations then disappear (Vignoles and Meschi 2010). There is some evidence that paying pupils for attendance, behaviour and results can reap benefits (Riccio 2010, Fryer 2010, Bettinger 2010). Such extrinsic motivation has no long-term effect on motivation, and cannot make a difference if the pupil does not have the competence to improve. There is, therefore, no reason to believe that teachers can generally improve educational outcomes for disadvantaged through motivation/attitude alone.    

Self-concept, self-esteem, self-efficacy, locus of control

Self-efficacy is an individual’s belief in their own ability, locus of control is their belief that their own actions can make a difference, self-concept is their perception of themselves, and self-esteem is an individual’s evaluation of their own worth or goodness. These sound very similar, and the research on them is inter-linked (Marsh and Craven 2006, Swann et al. 2007, Marsh and O’Mara 2008). They are not particularly stratified by SES, except perhaps by the sex of the individual (Meece and Painter 2008, Whitesell et al. 2009). As with most of the affective characteristics of pupils, there is some evidence of an association between school attainment and self-concept (Cervantes 2005, Peetsma et al. 2005, Skaalvik and Skaalvik 2009, Shavelson and Bolus 1981, Zand and Thomson 2005, Gonzalez-Pienda et al. 2002), or self-esteem (Bank and Spencer 1997). However, Baumeister et al. (2005) suggest that this correlation disappears once other factors are accounted for. There is slightly less evidence for the link between locus of control or high self-efficacy and attainment (Schulz 2005, Speight 2010, Da 2005).

There is considerable dispute about the sequence underlying these associations. Using very similar datasets and techniques, some commentators say that there is no causal sequence (Chowdry et al. 2010, Baumeister et al. 2003, Valentine and Dubois 2005), some that these mental constructs lead to school outcomes (Guay et al. 2004, Marsh et al. 2005), and some (including some of the same commentators) that the sequence is reciprocal (Chamorro-Premuzic et al. 2010. Pinxten et al. 2010, Marsh and O’Mara 2008, Baumert et al. 2005). The same is true for self-efficacy/locus of control, with some claims to the correct sequence leading to school outcomes (Bandura et al. 2001, Yailagh 2003), and some saying that the sequence is incorrect and the other way around (Tang 2004, Grabowski et al. 2001). It is as likely that educational outcomes lead to self-efficacy/locus of control as the reverse. The evidence is ambiguous, and should have been resolved by controlled intervention studies. There is a little evidence that programmes to improve self-concepts lead to improved attainment, at least in the short term (Cohen et al. 2009, Oyserman et al. 2006), and the same is true for self-efficacy (Hughes et al. 2006). Most studies are small, not randomized, and where they are reported the effect sizes are small. At present, it might be unwise to make pupils falsely believe that their future was under their control, or that their capabilities were great. What would be preferrable would be greater competence to control their world. Simply making people believe that they are more competent than they actually are may be ineffective or worse. But then making people more competent at gaining positive school outcomes is almost the same as simply improving their school outcomes. There is no reason to believe that teachers can generally improve educational outcomes for disadvantaged through factors like self-efficacy alone.

Improving behaviour

An individual’ behaviour is of concern where it is risky or disruptive (including poor attendance and punctuality). Such behaviour is slightly stratified by SES and by the school mix (Goza and Ryabov 2009). A focus on improving behaviour is unlikely to result in improved school outcomes but it may be a necessary pre-condition (Horner et al 2009). It could also have an added value for the rest of the pupils in the teaching group whose education would become less disturbed. Poor attendance, poor social relationships, and disruptive behaviour are all associated with attainment to some extent (Shin 2007, Vitaro et al. 2005, Crede et al. 2010). There is very little evidence relevant to the sequence from behaviour to attainment. For example, Beckett et al. (2012) showed a larger effect size of 1.25 for improved behaviour and a medium effect size of 0.68 for improved attainment. The randomised intervention was for parenting interventions with 171 pupils in England identified as at risk. This is impressive. However, this was a small study with high attrition, based only on parental reports. It was not so much a teacher intervention, and anyway the study cannot show that the change in attainment is caused by improved behaviour. Similar comments apply to Synder et al. (2010) who evaluated the effects of the Positive Action programme targetting student behaviour and character, with 544 students in public elementary schools, with around 25% receiving free or reduced price lunch. They showed moderate effect sizes for improved behaviour and attainment, but did not test the link between the two.

The association between the two appears pre-school anyway (Fantuzzo et al. 2003), and some interventions show no impact of imporved behaviour on attainment (Jones et al. 2011, Reback 2010). Despite this, a number of controlled interventions have shown promise (Gottfried 2010), and a very large review found consistent evidence of impact (Payton et al. 2008). See also (Bradshaw et al. 2010, Lassen et al. 2006, Flay and Allred 2003). Unfortunately, these interventions are often complex, involving changes to teaching as well as counselling and treatment for risky behaviour and poor attendance. This makes it hard to decide on what the ‘active ingredient’ is.

Therefore, at present, there is some evidence that improving behaviour is partly influenced by interaction with teachers, that it is associated with improved attainment, and may have wider benefits as well. There is promise here.


Well-being is a relatively new and disputed concept. Here it is assumed to encompass enjoyment and happiness, safety, psychological health, and social and emotional competence. As with so many characteristics discussed so far, enjoyment of education and school is not particularly stratified by the standard SES variables (Gorard and See 2011). It is more strongly linked to respect or concern by teaching staff, control of own learning, and poor (passive) teaching. There were many studies looking at the impact of social-emotional learning on students’ well being. Co-operative learning which links student wellbeing with academic and social-emotional learning with positive peer relationships has been associated with lower levels of bullying and increased levels of assertive problem-solving skills (Johnson et al. 2001). It has also been linked to improvements in academic outcomes, social skills, motivation acceptance of diversity, conflict resolution, self-esteem, self-control, positive attitudes to school and critical thinking (Johnson and Johnson 1989, Slavin 1995). A number of studies have shown that students’ pro-social behaviour predicts performance on standardised tests (Zins et al, 2004). Studies have also shown the positive associations between socio-emotional skills and social and academic success. Much reference was made to studies that showed positive associations between socio-emotional skills and academic achievements. However, many of these studies were studies of associations and were not able to show the causal link. It is possible that there might be other covariates (e.g. social class, parental attitudes) related to socio-emotional skills that were not accounted for in the models used in these studies. As with so many of these affective characteristics the sequence between them and attainment is unclear (Noble et al. 2008).

But few studies evaluated the impact of improvements in affective outcomes on academic performance, and even when they did, analyses often do not take into account potential covariates that might have accounted for the effect. Hence it is difficult to say if there was a causal effect of such interventions on academic outcomes. Certainly, the factors that are deemed to make a school successful academically are not those that make it supportive of well-being (Gray et al. 2011). Wright et al. (2010) evaluated a Teaching for Personal and Social Responsibility (TPSR) programme for a Wellness course in an inner city high school, with 122 African-Americans aged 14-18, of whom 99% were in receipt of free or reduced price lunch. Half were given the programme, and half were control, but these were not randomised. The behaviour, punctuality and attendance of the treatment group showed slight improvement. There was no clear impact on academic outcomes, either on the course or more generally.

However, there is still some promise here. Durlak et al. (2008) conducted a meta-analysis of 213 projects involving 270,034 students who were involved in a combination of programmes such as values/character education, anti-bullying prevention, conflict resolution training and resilience. Students were from kindergarten to eighth grade (age 14). On average, participation in social-emotional learning (SEL) programmes was linked to a 11 percentile points higher score on standardised achievement tests compared to those who did not, and the effects persist over time among studies where follow-up data were available. Possible confounds include extra teacher attention more generally, for academic learning, and more time to have better relationships with pupils. There is no standardised approach to measuring social emotional skills. Nevertheless, one of the most interesting findings is that the SEL programmes evaluated were of three kinds, those conducted by teachers, researches, and others including parents. Only those interventions conducted solely by teachers were found to be effective.

Citizenship, and democratic participation

The behaviour here includes participation in school and wider responsibilities, including school councils, voting and intention to vote, charity and other socially desirable voluntary work. This behaviour is not as stratified by SES as clearly as school outcomes are. In fact, some studies suggest that ‘softer’ school outcomes like learning to trust and developing a sense of justice are largely un-stratified by pupil background variables (Gorard and Smith 2010, Vyverman and Vettenburg 2009). There are strong associations between such activities and pupil reports of their interactions with teachers. It is probably not an exaggeration to say that civic participation cannot be taught. It can be encouraged and demonstrated. There is evidence that pupils’ growing sense of fairness could be influenced by individual interaction with teachers (Gorard 2012b). Elias and Haynes (2008) evaluated a Social Decision Making/Social Problem-Solving curriculum to promote social-emotional competence, with 282 urban elementary pupils, mostly African-American, 60% in receipt of free or reduced price lunch. This non-experimental design showed an association between academic performance and perceived teacher support.


Unfortunately there is either no evidence for, or there is evidence against, proceeding with pupil characteristics such as motivation/attitude, self-esteem/self-concept, or aspirations/expectations. These factors may be desirable in themselves and they may be malleable to some extent through interaction with teachers. But we cannot say that they lead to improved attainment or participation in education. It is more likely that these ‘softer’ outcomes would be the result of improved success at school, which should therefore be addressed directly or in some other way. How such characteristics could be measured also becomes a moot point.

Intriguingly, it is the more visible and tangible processes such as pupil behaviour, citizenship activities and perhaps well-being that show the most promise. The interventions cited here would be a good place to start if looking for teaching approaches that might yield success in these areas, and also for examples of scales and measures that could be adapted for easy use. They may lead to enhanced attainment, are desirable in their own right and have obvious beneficial consequences for others. Preventing disturbance in class benefits the individual pupil and their peers, encouraging civic participation is presumably healthy for society, and preventing bullying prevents bullies as well as bullied, for example. Improvement in all of these areas is made more possible because of the low levels of SES stratification compared to attainment and participation. The key common element in the relevant studies is the nature of interactions between pupils and teachers. Pupils are quite clear what the rules should be (Gorard and Smith 2010). A meta-analysis of over 100 studies (Marzano et al. 2003) found that the pupil-teacher relationship was the most important factor in effective classroom management and students’ engagement in learning.


Measurements of affective outcomes  

Measures of affective outcomes can take the form of observed and self-reported or teacher-reported improvements in conduct behaviour, social competence, peer and teacher relationships. Conduct behaviour includes attendance, suspension, progression to the next grade, discipline referrals.  For example:

  • Students may be simply awarded a conduct ratings of excellent, satisfactory, needs improvement or unsatisfactory by the instructor (Wright et al 2010).  Positive behaviour was defined as the total number of excellent and satisfactory ratings, while negative behaviour was the total number of needs improvement and unsatisfactory ratings.
  • Truancy and tardiness measured by the number of times students were late or absent both in the Wellness class and overall (Wright et al 2010). In Wright et al’s study these were based on teacher/instructor reports.
  • Absenteeism measured by the average number of days absent per year (Snyder et al 2010)
  • Suspensions (percent suspended) which could be due to disorderly conduct, burglary, truancy or possession of contrabands, such as tobacco and drugs and retention (kept back in grade) (Snyder et al 2010). In Snyder et al’s study these indicators were collected from school archival data.

Social adjustment or social competence includes respect for rights of othersself-motivation, caring, self direction.

  • In Wright et al’s study (2010) affective outcomes like respect for rights of others, self-motivation, caring, self direction were measured using a checklist where students indicated whether the instructor had promoted these measures. Teacher ratings were also taken to confirm students’ assessments. An example could be the instructor noted that students ‘were working without direct supervision and they are having fun’.
  • Assessments could also be in the form of a checklist (Wright etl al 2010). E.g. students could be given a goal-setting sheet where they indicate whether they had set goals related to truancy, tardiness or conduct or academic performance, such as passing or getting a better grade in specific subjects. (Note that no examples of the actual instrument were given in the paper).
  • In Elias et al’s study (2008), social-emotional competence was measured using a 28-item Social Skills Rating Scale (SSRS) which measures, cooperation, assertion and self-control (SSRS; Gresham & Elliot, 1990). The instrument was not included in the paper. This was completed by the teachers.
  • In Ben-Avie and Steinfeld’s (2001) study students’ youth development was measured using the Youth Development and Student Learning Inventory (YDSL) (Ben-Avie and Haynes, 1998, 1999). This is a 112-item, 5-point likert scale response inventory that measures 4 dimensions of student learning and youth development (measures engagement with adults, peer bonding, coping and professional conduct).

For example, coping was measured asking students to what extent they agreed with questions like:

- If I think that a classroom rule is unfair, I am able to respectfully get a teacher to consider changing it.
- Many times when two of my friends have argued, they have asked me for my help in settling the argument.
- When there is a conflict between two adults in my family, I am unable to do my schoolwork.

  • In the Alberta Department of Education (1993) project, academic, social and behaviour data together were used as indicators of students’ character development. Student behaviour was measured using homework completion rates, vandalism and discipline. Student survey and telephones were conducted on students’ perceptions of student behaviour within the school district. Responses were based on the extent to which students agreed with each of the statements:

- The students got along with each other
- It was easy to make friends in all schools
- The school(s) motivated students to do their best
- Students received satisfactory recognition for specially responsible behaviour
- Values being taught in all school(s) were satisfactory
- The school did a good job in helping students understand their moral and ethical responsibilities.

From these surveys (including students, teachers and community surveys) indicators for responsible student behaviour were developed which included high expectations, mutual respect, recognition, pride, courteousness, caring, sharing, mutual trust and open communication.   Peer and teacher/student relationships In other studies students’ perception of social support provided by the school and their perceptions of their teachers were also used as indicators of teacher/student relationship, peer relationship and adult engagement.

  • In Elias et al’s study (2008), Social Support was measured using the Survey of Children’s Social Support (SOCSS), a multi-dimensional assessment of perceived family, peer and teacher support. Examples of items include:

- Do your teachers make you feel important?
- Do you think your teachers care about your?
- Do you get picked on and teased by your friends?
- Do you feel left out by your friends?

  • In Ben-Avie and Steinfeld’s (2001) study Youth Development and Student Learning Inventory (YDSL) (Ben-Avie and Haynes, 1998, 1999) was used to measure the 4 dimensions of student learning and youth development (engagement with adults, peer bonding, coping and professional conduct). This is a 112-item, 5-point likert scale response inventory

Adult engagement was measured with questions like:

- When I am having some type of crisis during the school day, an adult is there for me.
- When I am making a decision about my future, I get advice from an adult at school. Student-teacher relationship was measured using items like:
- I make less of an effort in a class when I do not like the teacher.
- Teachers gave me enough personal encouragement in my school work.
- Teachers liked the children and were fair when dealing with them.
- Teachers encouraged me to do my best and tried to help me improve.
- My teachers are willing to give students individual help outside of class time.

  • In the study by the Alberta Dept of Education (1993), aspects that students liked about their teachers were: friendly, supportive, willing to help, small classes, honesty, enthusiasm, caring, competence, closeness with students.

Aspects students disliked included teachers having favourites, losing temper, too many clique, been in position too long/lack motivation, don’t know subject matter, don’t push hard enough, lack of proper moral behaviour, gossip too much, needs role-modelling. Discipline needs to be fair and consistent. Teachers should be viewed as authority figure rather than punishment maker.

Self-concept, self-efficacy, self-esteem, locus of control

There are no straightforward ways of measuring these affective outcomes as there is no consensus as to what they actually mean. As a result different instruments were developed, adapted and modified. These ranged from Shavelson’s short Self-Description Questionnaire II (Marsh and Shavelson, 1985), Multi-dimensional Self-Concept Scale (MSCS) and the Academic Motivation Scale (AMS) (Zanobini & Usai, 2010), Rosenberg (1965) self-esteem scale, psychometric tests, Student Motivation and Engagement Scale (Martin, 2003) and General Achievement Goal Orientation Scale (GAGOS) to the use of variables adapted from longitudinal survey data (e.g. Keith & Cool, 1992).   To demonstrate the complexity of these affective measures, see below for examples of studies using the different measures of these alternative outcomes:


Baumeister et al (2005) defined self-esteem as a perception as a person’s belief about themselves, i.e. whether they are intelligent or attractive. It is ‘how much value people place on themselves. It is the evaluative component of self knowledge. High self-esteem refers to a highly favourable global evaluation of the self. Low self esteem, by definition, refers to an unfavourable definition of the self.’ (p. 2). Others argued that self-esteem is simply a global component of self-concept (Marsh & Craven 2006), and that self-concept is both descriptive and evaluative. This suggests that their definition of self-concept would include self-esteem. In other, words, self-esteem is one component of self-concept. The examples they used were: “I am good at mathematics”, “I can run a long way without stopping”, and “I am good looking” are both evaluative and descriptive. These statements are simply a reflection of different aspects of self-concept (math self-concept, physical and appearance self-concept).


Shavelson. et al (1976) defined self-concept as a person’s perception of themselves as a result of their experience, and is reinforced by evaluations of significant others.  Their model of self-concept is both multifaceted and hierarchical.  As such, their study selected one subscale on each instrument to represent each facet (physical, social and academic).  They also believed that general self-concept is more stable over time than academic self-concept, and academic self-concept is more stable than self-concept in specific academic areas (e.g. self-concept in maths).  Academic achievement in a specific subject should correlate highest with self-concept in that subject. They also noted that self-concept is both an outcome and a mediating variable.

Marsh and Craven believed that self-concept is multidimensional, and that ‘academic achievement is substantially related to academic self-concept, but nearly unrelated to self-esteem.’ (p. 133). They argued that ‘the most powerful effects of self-concept are based on specific components of self-concept most logically related to specific outcomes (a multidimensional perspective), rather than on the global component of self-concept represented in global measures of self-esteem (a unidimensional perspective).’ (p. 134)

Zanobini and Usai’s study used the terms ‘self-concept’ and self-esteem’ interchangeably depending on the authors they are citing. But their operative definition is a multidimensional self-concept which subsumes the evaluative and descriptive components. Self-concept and motivation were measured using the self-completed Multi-dimensional Self-Concept Scale (MSCS) and the Academic Motivation Scale (AMS). The AMS scale measured extrinsic and intrinsic motivation, as well as, lack of motivation (amotivation). Academic achievement was measured using teacher-assessed final school grades.   Self-efficacy Grecas (1989) defines self-efficacy as a belief in one’s ability or competence, while self-esteem is an evaluation of one’s worth or goodness. The latter is not directly linked to one’s ability as it could be derived from one’s physical attractiveness, personality or moral behavior. Self-efficacy, in turn, influenced one’s aspirations and attitudes towards school.   While some authors refer to self-worth as self-efficacy (Cohen et al. 2009), Hughes et al. (2006) used a battery of psychometric tests (general self-efficacy, subject specific self-efficacy, self-esteem and academic motivation) as indicators of self-concept.


In Zimmerman et al’s study (1992) they used self-efficacy to mean students’ perceived self-efficacy for academic achievement. Their study used the multidimensional scales for measuring perceived self–efficacy for academic achievement and self-efficacy for self-regulated learning. The latter measured students learning strategies, such as resisting distractions, motivating themselves to complete school work and participating in class. The former assessed students’ beliefs in their own ability to learn a number of course work, e.g. math and language.   Therefore, when discussing self-esteem/self-efficacy in relation to academic attainment, some researchers argued that it is useful to differentiate between global self-esteem, which promotes general well-being, from domain-specific self-esteem (e.g. academic self-esteem). The latter is believed to be a more accurate predictor of school performance (Rosenberg et al 1995, Marsh and Craven 1997 and Shavelson et al. 1976).

Self-concept and Motivation

As self-concept and motivation are closely related (OECD, 2003, p. 9), some studies have also examined the combined reciprocal effects of motivation and self-concept (e.g. Marsh et al., 2005; Skaalvik & Valås, 1999).  Both studies use ‘interest’ as a measure of motivation.   Skaalvik & Valås (1999) defined math motivation as ‘interest in working or liking to work with tasks, in math (p.139). In addition, motivation was also measured in terms of the amount of effort and time invested in the subject. It is defined as making an effort and not giving up easily on math. Examples of questions included: ‘I give up easily if I get a difficult math task’. Although this study, like Marsh and others used specific academic self-concept, they define self-concept as a ‘general feeling of doing well or poorly’ (p.139) in the subject. Examples of questions were: ‘I always do well in math’, and ‘I am hopeless in math’.

Green et al (1984) measured student motivation and engagement using the Student Motivation and Engagement Scale (Martin, 2003). This was a self-completed instrument designed to measure students’ adaptive and cognitive behaviour, such as, self-efficacy, mastery orientation, and valuing of subject, persistence, planning, and study management, as well as, anxiety, failure avoidance, and uncertain control. Maladaptive behavioural dimensions (e.g. self-handicapping and disengagement) were also measured.Self-concept was measured using Shavelson’s short Self-Description Questionnaire II (Marsh and Shavelson, 1985).

Dowson et al (2003) used the General Achievement Goal Orientation Scale (GAGOS) developed by one of the authors McInerney (1997) to measure motivational goals. This instrument specifically measures 3 areas of achievement motivation: General Mastery (e.g. “I am most motivated when I see my work improving”); General Performance (e.g. “I am most motivated when I am doing better than others”), and General Social (e.g. “I am most motivated when I work with others”). Academic self-concept was measured using a modified version of Marsh’s (1992) Self-Description Questionnaire II (SDQ II) (Marsh, 1992), (eg. “I am good at English/math”).

Keith and Cool (1992) used the National Center for Education Statistics’ longitudinal data. They selected items from this data that measured quality of instruction and motivation constructs. However, the authors expressed doubts about whether students’ responses to questions about the quality of their school and its instruction actually measure quality of instruction and schooling. The order in which the variables were included in the model was based on a logical and chronological sequence and also on previous theory and research. Hence, background variables and ability were entered first before the other variables. Quality of instruction came before motivation as a high quality instruction generally leads to higher motivation, and a highly motivated student, in turn, complete a more academically oriented curriculum.  Students in a more academic curriculum should complete more homework and therefore achieve a higher level.


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