Development and Validation of the Academic Hope Scale (AcHS) for Students

doi:10.21203/rs.3.rs-4968417/v1

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Development and Validation of the Academic Hope Scale (AcHS) for Students

https://doi.org/10.21203/rs.3.rs-4968417/v1

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Since the majority of hope-related instruments constructed so far assessed the general concept of hope in life, developing the academic hope scale can provide valuable information in academic fields. The present study aimed at developing and validating of academic hope scale in student samples at schools and universities. This scale consisted of 27 items which extracted from the results of interviews with high school and university students and based on the theoretical foundations of Snyder’s (1994) and Pekrun’s theories (2006). The psychometric properties of this scale were examined in two studies. 241 high school students and 566 bachelor’s students are selected through the multi-stage random cluster sampling method in the first and second studies, respectively. The results of the exploratory factor analysis in the first study in which principal component analysis (PC) was used, showed that there were 4 components of academic hope, namely hope to gain opportunities, hope to gain life skills, hope in school’s usefulness, and hope to gain competency. In the second study, the results of the confirmatory factor analysis confirmed the existence of the 4 components of academic hope. The Cronbach's alpha coefficients in the first and second studies showed high levels of scale reliability. In general, the results indicated that the AcHS had appropriate reliability and validity in both school and university populations and could be used as a useful tool for measuring academic hope in various academic groups.

Academic Hope

Academic Well-being

Control–Value Theory

Achievement Emotion

Hope as a psychological construct emerged in psychological texts in the 1950’s and was emphasized as a mechanism for therapeutic changes, to encourage learning, and to support general well-being (1). An individual with hope has the successful agency and the plans and motivation required for achieving goals (2). They know what they want and are also well aware of the way and the means to achieve them. In the face of challenges, an individual with hope tries to pursue their goals another way. Many instruments have been designed for assessing hope and hopefulness, especially in adult populations (1). For example, the Miller Hope Scale (MHS) was developed by Miller and Powers (1) as a way to measure hope in patients with various health conditions. There have been additional scales of hope developed beyond the MHS. Snyder (2) developed hope scale, comprising of 12 items and two aspects, namely strategic thinking (pathway) and agency thinking. Snyder (2) introduced hope like a procedure of thinking about reaching a goal with motivation for moving towards the goal (agency) and the ways of achieving it (pathway). In fact, Snyder believed that two types of thinking (pathway and agency) were required to create hope. Strategic thinking (pathway) was defined as a cognitive constituent of hope which indicated the individual’s capacity and ability for creating a pathway, while agency thinking was the motivational component of hope through which an individual was provoked to make use of the pathways (3). According to Snyder (2), hope is a dynamic motivational-cognitive system. It is an individual’s ability to set goals as well as imagining the pathways and having required motivation for achieving those goals. In other words, as stated by Snyder, to achieve success in challenging tasks one often needs the ability to create several pathways for achieving the goals (4, 5).

There are several psychological mechanisms that underlie and shape hope. Snyder (2) dealt with hope from a cognitive perspective. Then, Pekrun (6) came up with an emotional perspective to hope, and argue that hope is more emotional in nature. In Pekrun’s control-value theory (6), hope is considered a prospective consequential emotion arousing an individual to make progress. In consequential emotions, success has positive value and failure is negative. Thus, people will feel hopeful if they feel they have relative control over a situation and there is the prospect of success. But, if success is considered inaccessible and the individual feels little control over the situation, they will experience despair and hopelessness (7). In fact, when an individual is focused on lack of achievement, and failure seems unavoidable, they will feel frustration. In Pekrun’s control-value theory, frustration is classified as a negative outcome-driven and passivizing emotion, whereas hope is categorized as a positive outcome-driven and activating emotion (8). It is worth mentioning that the majority of the studies carried out on hope during the recent two decades have been conceptualized based on Snyder’s theory of hope (9). Therefore, most of the studies investigated hope from a cognitive-motivational perspective and it was less often considered from cognitive-emotional perspectives. However, hope as an emotion plays an important role in various situations. The emotion may lead one to design ways to achieve their goals (10).

As mentioned previously, the present study aimed at investigating the role of hope as an emotion in a specific area, the academic field. Thus, academic hope is a cognitive-emotional construct and refers to how an individual looks forward to a pleasant event related to their academic endeavors. In fact, academic hope is defined as an emotion and expectation based on the idea that an individual can gain access to occupational and social opportunities as well as success in the future via their education (11).

Several studies have investigated the role that hope can have in academic achievement. For example, Irving, Snyder & Crowson (12) showed that teaching students how to increase their feelings of hope can have psychological benefits for these students. They found that students experiencing high degrees of hope on the Adult Hope Scale also reported high levels of well-being, academic performance, coping strategies, and regulation of emotional distress. Snyder, Sympson, Michael and Cheavens (13) demonstrated that hope was a means by which people could prevent the emergence of other problems in life. Similarly, hope is correlated with overall life satisfaction (14). In addition, it has been suggested in numerous studies that psychological hardiness has significant relationship with hope in life and academic performance (15, 16). The results of several studies (17–19), indicate that academic hope has a relationship with students’ hard work and academic activities. On the other hand, it has been suggested in these studies and others that hope is positively associated with high academic performance and achievement in school (19–23). More adaptive academic behaviors were observed from the students with high degrees of hope compared to their peers with lower hope (24). Although the issues and challenges related to academic success have been well indicated, less attention has been paid to schools’ abilities in promoting the advantages of students’ natural competencies (including self-efficacy, hope and problem-solving). These nonacademic characteristics can positively influence academic success at school and also have an effect on healthiness, happiness and later success in life (23, 25).

In validating the questionnaire on hope in children, Snyder (26) pointed out that there was a positive relationship between high scores of hope in future and high exam marks. Furthermore, research evidence indicated that hope-teaching interventions could enhance hope levels (26, 27). For example, the relationship between hope and higher levels of competency in many life areas such as education was investigated (3, 5, 23). That is, hopeful students were more likely to believe that they would obtain their intended final exam marks. In fact, university students with higher hope levels were found to have higher levels of trust in their own academic competencies compared to students with lower levels of hope (28, 29). Previous research that we have discussed, above, clearly indicates that hope is an important component in motivating students toward academic achievement (30). Therefore, the use of a valid and reliable tool for assessing feelings of hopefulness in students can be a valuable tool for supporting academic achievement. Existing hope assessment instruments developed by Snyder (2) and Miller & Powers (1) were designed to be used with a general population of adults and a targeted population of adults with health conditions, respectively. There is a need for a reliable and valid instrument for measuring hope that is specific to the sense of academic hope felt by students.

The primary goals of the present study were to investigate academic hope in a sample of high school (Study 1) and university students (Study 2) and to develop a psychometric academic hope scale that may be used in educational contexts.

3. Methods

Before interacting with any participants, we submitted our study protocol, survey materials, and interview questions to both the Shiraz University Research Ethics Review Committee and to the school administrators for each of the high schools from which we recruited participants. Each review committee granted us permission to conduct the study with their students as participants. In addition, we ensured that all participants knew that their participation was voluntary and that they would not incur any negative repercussions for choosing not to participate.

3.1. Population, Participants and Sampling

The respondents in Study 1 were 241 primary and secondary school students (137 Male and 104 Female) from two districts of the Department of Education in Shiraz city. The samples were selected through a multi-stage random cluster sampling method from the four districts of the Department of Education. To this end, two districts (districts 2 and 4) were initially selected from among the four districts and subsequently two schools, a girls’ school and a boys’ school, were selected. Next, a class from each secondary school grade was randomly selected in each school and the participating students within each of these selected classes were entered into the study as participants. In addition, the mean age of the participants was 16.52 and its standard deviation was 1.45. The participants were at least 14 and at most 20 years old.

3.2. Instruments

Creating the AcHS

In the present study we used an exploratory-sequential mixed-method to construct the current scale. To do this, we conducted semi-structured in-depth interviews with 20 students. We asked them questions about academic hope, such as “what is hope and what do you hope to achieve by studying?” We analyzed the students’ answers using the conventional qualitative content analysis method, and the key concepts were extracted. Next, 40 items were extracted based on theoretical foundations of Snyder’s theory (2) and Pekrun’s control-value theory of achievement emotion (6) as well as the key concepts extracted from the interviews with the students. In the next stage, we analyzed the content and face validity of the items on the questionnaire by asking experts among the psychology department faculty at Shiraz University to evaluate the appropriateness of each item. In the end, 27 out of the 40 items were selected and verified among these experts, and the rest of the items were discarded or merged into an existing item. Each of the 27 items on the scale were written as Likert scale questions, with responses ranging from 1 (completely disagree) to 5 (completely agree). The valence of items 6, 9, 10, 11, 13, 21, 24 and 27 were written in order to be scored inversely. After the questionnaire was administered, we analyzed the psychometric properties of the scale using exploratory factor analysis.

In addition to the academic hope scale used to assess the criterion validity, the following scales were also used with regard to the related literature: 1) children and adolescents patience scale (31) and 2) psychological hardiness scale (32).

4. Results

To investigate the validity of the AcHS, we conducted an exploratory factor analysis and calculated the Pearson’s correlations between the other scales like the patience scale and psychological hardiness scale with the subscales (hope to gain opportunities, hope to gain life skills, hope in school’s usefulness and hope to gain competency) and total test scores of AcHS. In addition, we calculated the Cronbach’s alpha on the reliability of responses across the AcHS.

4.1. Validity of Academic Hope Scale (AcHS)

Factor analysis to identify principal components. Before conducting our factor analyses, we examined whether or not the assumptions of factor analysis were met. That is, we examined whether the data met the assumptions of normally distributed data, lack of collinearity, and the elimination of outliers. The data appeared to meet all the necessary assumptions for us to proceed with performing a factor analysis (33). To determine the validity of the AcHS, we conducted a principal components analysis along with varimax rotation of factors. Our analyses indicated that the KMO coefficient (Kaiser-Meyer-Olkin measure of sampling adequacy of 0.926) and Bartlett’s test of sphericity (3536.29) reflected sufficient evidence for performing factor analysis. To determine the number of factors, we examined the Scree plot which indicated the existence of 4 factors as the components of the academic hope scale. The results of the factor analysis and factor loading of each item on each factor are presented in Table 1.

Table 1

the results of factor analysis of academic hope scale based on principal components with varimax rotation
Item number	Factor 1	Factor 2	Factor 3	Factor 4
2	0.79
1	0.79
8	0.66
4	0.61
3	0.61
5	0.61
14	0.57
25		0.74
22		0.73
23		0.73
16		0.68
17		0.67
19		0.59
20		0.55
7		0.48
21			0.72
24			0.69
9			0.67
10			0.62
27			0.58
11			0.54
6			0.42
13			0.36
26				0.75
12				0.74
15				0.63
18				0.59
Eigenvalues	4.97	4.38	3.62	2.57
Variance percentage	18.43	16.23	13.44	9.52
Total variance percentage	57.63

Based on the factor analysis, we identified four components of the academic hope scale. Each of these components was named based on the study items which loaded onto that factor. The first factor was named “hope to gain opportunities”. It indicated the existence of the hope and expectation an individual had for achieving occupational and social opportunities as well as success in their future life. Items such as “I can find an appropriate job in the future via schooling” assessed this component. Items 1, 2, 3, 4, 5, 8, and 14 assessed this factor.

The second factor was called “hope to gain life skills”. It referred to the hope and expectations students had that what they were learning at school would provide them with critical thinking skills and the skills for living in the community and interacting with others. Such items as “Whatever is taught to me at school will provide me with thinking skills.” expressed this factor. Items 7, 16, 17, 19, 20, 22, 23 and 25 assessed this component.

The third factor was called “hope in school’s usefulness”. Items such as “working in the market and being self-employed teach us more skills than spending time in school”, assessed the component of “hope in school’s usefulness”, which encompassed the hope and expectation that schooling and education were useful in having a good life and finding an appropriate job. Items 6, 9, 10, 11, 13, 21, 24 and 27 investigated this component.

Finally, the fourth factor was called “hope to gain competency”. Items such as “schooling will be followed by prestige and popularity for educated individuals” is an indicators of this component. Hope to gain competency reflected the hope and expectations based on which an individual anticipated they would obtain social reputation, popularity and prestige due to their education level. The component was assessed by items 12, 15, 18 and 26.

The results of the factor analysis indicated that the first factor (hope to gain opportunities), with an eigenvalue of 4.97, accounted for 18.43% of the total variance. The second factor (hope to acquire life skills), with an eigenvalue of 4.38, explained 16.23% of the total variance. The third (hope in school’s usefulness) and the fourth (hope to gain competency factors with eigenvalues of 3.62 and 2.57 also accounted for 13.44% and 9.52% of the total variance of the scale, respectively. The four subscales of the academic hope scale explained a total of 57.63% of the whole sample volume’s variance.

Calculation of the correlation between subscales and total test score

Another method used to evaluate construct validity is the calculation of the correlation between the subscales and the total test score (34). Furthermore, to assess the convergent validity of the academic hope scale with regard to the research background, its correlation with such scales as patience and hardiness was examined, the results of which are shown in table (2).

Table 2

correlation matrix of the study variables in the first study
Variables	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1-psychological hardiness	45.29	8.51	1
2-hope to gain opportunity	28.17	6.35	0.18**	1
3-hope to gain life skills	29.56	6.79	0.10	0.72**	1
4-hope in school’s usefulness	26.30	6.37	0.25**	0.67**	0.58**	1
5-hope to gain competency	15.54	3.39	0.14**	0.56**	0.57**	0.36**	1
6-total score of academic hope	99.59	19.25	0.20**	0.90**	0.88**	0.82**	0.68**	1
7-sublimation	24.00	5.32	0.14*	0.63**	0.56**	0.47**	0.48**	0.65**	1
8-forbearance	14.17	3.31	0.13*	0.22**	0.25**	0.23**	0.12	0.26**	0.16*	1
9-acceptance	11.36	3.17	0.24**	0.21**	0.20**	0.24**	0.12	0.24**	0.20**	0.35**	1
10-persistence	33.52	8.09	0.30**	0.42**	0.32**	0.46**	0.18**	0.43**	0.41**	0.17**	0.26**	1
11-hesitation	33.69	9.02	0.21**	0.32**	0.17**	0.35**	0.07	0.30**	0.31**	0.01	0.07	0.68**	1
12-total patience score	116.74	20.15	0.30**	0.55**	0.43**	0.54**	0.27**	0.56**	0.63**	0.34**	0.40**	0.88**	0.82**	1
P < 0.05 and *P < 0.01

The results of the correlation matrix showed that there was a positive relationship between psychological hardiness and hope to gain opportunities, hope in school’s usefulness, hope to gain competency, total hope score, acceptance, persistence, hesitation and total score of patience at the significance level of p < 0.01. Also, there is a positive relationship with sublimation and forbearance (two subscales of psychological hardiness) at p < 0.05. On the other hand, all the patience subscales and the four academic hope subscales had a positive correlation with the total scores of patience and academic hope at p < 0.01. The results also indicated the construct validity and convergent validity of the AcHS. That is, the results of the correlation matrix showed that the total hope score had positive and significant relationships with all its subscales (p < 0.01). Furthermore, the correlation between academic hope subscales was lower than the correlation between each of the subscales with the total hope score. This confirmed the discriminant validity of the subscales with one another and the convergent validity of the subscales with the total score of hope. We found a positive and significant correlation between respondents’ scores on the academic hope scale with their scores on the children and adolescents patience scale (31) and with the psychological hardiness scale (32). In fact, the results of the internal consistency provided evidence of the convergent validity of the AcHS with measures of patience and psychological hardiness.

4.2. Reliability of Academic Hope Scale

To assess the reliability of the academic hope scale, the internal consistency of the items and the Cronbach’s alpha coefficient were used, the results of which are presented in table (3).

Table 3

Cronbach’s alpha coefficients for the indicators of academic hope scale
Factors	Number of items	Cronbach’s alpha coefficient
Hope to gain opportunity	7	0.90
Hope to gain life skills	8	0.90
Hope in school’s usefulness	8	0.80
Hope to gain competency	4	0.76
Total score of academic hope scale	27	0.94

As observed in Table 3, the Cronbach’s alpha coefficients for the subscales of hope to gain opportunities, hope to gain life skills, hope in school’s usefulness and hope to gain competency were 0.90, 0.90, 0.80, and 0.76, respectively. The total Cronbach’s alpha coefficient was also 0.94 for the AcHS, suggesting that the scale had favorable reliability.

3. Method

As with Study 1, our study protocol was initially reviewed and approved by the Shiraz University Research Ethics review committee. All participation was voluntary.

3.1. Population, Participants and Sampling

The study population included BA students from Shiraz University. According to Kline’s approach (33) to determine the sample size, ten-to-one rule was applied. it means that at least between ten to twenty subjects should be selected per each model parameter. Thus, the study participants were 566 university students (278 men and 288 women) selected through multi-stage random cluster sampling. To do so, the samples were drawn from all of the faculties in the university. Two classes from each faculty member were randomly selected as the study samples, from these classes students were invited to participate. The mean age of the subjects was 20.95 years, and its standard deviation was 2.95 years.

3.2. Instruments

The Academic Hope Scale (student form) (11), hope subscale from achievement emotions questionnaire (35), schoolwork engagement inventory (36), school burnout inventory (37), and admiration scale (38) were used in this study.

Results

To analyze the data, Pearson correlation coefficient and confirmatory factor analysis for validity and cronbach’s alpha coefficient for reliability of scale were used.

4.1. Construct Validity via Factor Analysis

In this study, the AcHS (student form) was modified following the interviews with the university students in order to be used for students of various ages. The AcHS (university student form) contained 27 items, scored as completely disagree = 1, disagree = 2, neutral = 3, agree = 4, and completely agree = 5. To investigate the validity of the AcHS in this research, the confirmatory factor analysis (through maximum likelihood method) was applied; also, the Cronbach’s alpha coefficient was used to evaluate its reliability. The results of the confirmatory factor analysis using the AMOS software (version 21) indicated that all the items had significant factor loads of > 0.45 (minimum acceptable load was 0.32; Kline, (33); p < 0.001). The items were loaded onto their corresponding factors in such a way that items 1, 2, 3, 4, 5, 8 and 14 (with the factor loads of 0.50 to 0.78), items 7, 16, 17, 19, 20, 22, 23 and 25 (with the factor loads of 0.50 to 0.73), items 9 ,10, 11, 21, 24 and 27 (with the factor loads of 0.50 to 0.82), and items 12, 15, 18 and 26 (with the factor loads of 0.66 to 0.71) were loaded on “hope to gain opportunities”, “hope to gain life skills”, “hope in school’s usefulness”, and “hope to gain competency”, respectively (See Fig. 1). Due to their low factor loads in the confirmatory factor analysis, items 6 and 13 of the “hope in school’s usefulness” subscale were excluded from the scale.

The fit indices of the confirmatory factor analysis model are shown in table (4).

Table 4

fit indices of confirmatory factor analysis model of academic hope scale
Index	X²	df	X²/df	GFI	CFI	NFI	IFI	TLI	RMSEA	PCLOSE
Amounts	517.56	236	2.19	0.92	0.95	0.91	0.95	0.93	0.04	0.62

The model was estimated using seven fit indices. The results of all the seven indices indicated that the model produced favorable fitness. The Chi-square (x2) was 517.56 (P < 0.001, df = 236) and the ratio of the chi-square to degrees of freedom (2.19) was found to be in an acceptable fit range (1 to 3, Kline, (33)). The goodness of fit indicator (GFI) was 0.92 (acceptable values are larger than 0.90, Kline, 2015). The comparative fit indices CFI, NFI, IFI and TLI were found to be 0.95, 0.91, 0.95 and 0.93, respectively (acceptable value: >0.90; Kline, (33)). The RMSEA was 0.04 (acceptable value: <0.08; Kline, (33)) and the confidence interval of 90% showed a boundary range of 0.04 to 0.05 for it; in addition, the PCLOSE was 0.62 for this index (acceptable value: >0.05; Kline, (33)).

4.2. Correlation of academic hope scale with other tests

The other method used for evaluating the construct validity was the calculation of the correlation between the subscales and the total test score as well as the convergent and discriminant validity rates (34). Table 5 shows the correlation coefficients between the study variables. To calculate the convergent validity, the hope subscale on the achievement emotion questionnaire (35), academic engagement inventory (36), and admiration scale (38) were employed; the school burnout scale (37) was also used for the evaluation of the discriminant validity.

Table 5

correlation matrix between study variables in the second study
Variables	M	SD	1	2	3	4	5	6	7	8	9
1-school burnout	18.37	6.35	1
2-academic engagement	18.52	6.33	-0.50**	1
3-admiration emotion	15.48	2.26	-0.13**	0.30**	1
4-Pekrun’s hope	54.74	8.49	-0.46**	0.61**	0.31**	1
5-opportunity gain	29.07	4.25	-0.27**	0.33**	0.25**	0.46**	1
6-life skills	30.28	5.10	-0.26**	0.34**	0.24**	0.48**	0.68**	1
7-school’s usefulness	20.91	4.52	-0.43**	0.30**	0.11*	0.33**	0.38**	0.37**	1
8-competency gain	16.07	2.46	-0.16**	0.20**	0.18**	0.32**	0.67**	0.57**	0.23**	1
9-academic hope	96.33	12.91	-0.38**	0.39**	0.25**	0.52**	0.86**	0.86**	0.67**	0.72**	1
P < 0.05; *P < 0.01

As observed, Table 5 represents the results of the correlation matrix between the study variables. The results suggested that there was a positive and significant correlation between the AcHS score and academic engagement (r = 0.39, p < 0.01), admiration emotion (r = 0.25, p < 0.01) and the hope subscale from the AEQ (r = 0.52, p < 0.01); it also had a negative and significant relationship with school burnout (r= -0.38, p < 0.01). These results provide some evidence of the convergent and discriminant validity of the academic hope scale in respect to other instruments.

Another piece of evidence supporting the construct validity of an instrument is the correlation between the subscales and the total score of that instrument. That is, there should not be a high correlation between the subscales, the correlation should be moderate (0.50) and not indicating multicollinearity, because high correlations between subcomponents of a scale might mean that all the subscales assess one component. It is also better for the subscales to have a high correlation with the total score to indicate the validity of the scale construct (34). Hence, the results indicated that there was a moderate correlation between the AcHS subscales with one another, and the total score of academic hope had a positive and significant correlation with all its subscales (p < 0.01).

4.3. Reliability of academic hope scale via internal consistency

To assess the reliability of the AcHS, the internal consistency between the items and the Cronbach’s alpha coefficient were used, the results of which are shown in Table (6).

Table 6

Cronbach’s alpha coefficients for components of academic hope scale
Factors	Number of items	Cronbach’s alpha coefficient
Hope to gain opportunity	7	0.86
Hope to gain life skills	8	0.84
Hope in school’s usefulness	6	0.75
Hope to gain competency	4	0.80
Total score of academic hope scale	25	0.90

The Cronbach’s alpha coefficients of the AcHS were 0.86, 0.84, 0.75, 0.80 and 0.90 for hope to gain opportunities, hope to gain life skills, hope in school’s usefulness, hope to gain competency and the overall academic hope scale, respectively. In general, the results of Cronbach’s alpha coefficients reflected the favorable reliability of the academic hope scale.

5.1. First Study

The aim of this study was to develop and validate the Iranian version of the academic hope scale in Student Samples. Hope is a general concept; thus, to assess the hope-specific areas, using specialized instruments seems necessary. Academic hope scale well be one of the instruments used to respond to the needs of researchers in the field of education. In the first study, the results generally confirmed the existence of four factors (hope to gain opportunities, hope to gain life skills, hope in school’s usefulness, and hope to gain competency).

In an investigation of the convergent validity of the academic hope scale considering the study background, the correlation between academic hope scale and psychological hardiness and patience was examined. The results of the correlation matrix indicated that there was a positive and significant correlation between psychological hardiness and hope to gain opportunities, hope in school’s usefulness, hope to gain competency and the total hope score. Psychological hardiness is a psychological component associated with hope. It was found out in several studies that there was a positive and significant relationship between psychological hardiness and life expectancy and academic performance (15). In addition, the results of the several studies (17, 18, 39) suggested that there was a positive and significant relationship between psychological hardiness and academic performance and achievement. The positive and significant relationship between psychological hardiness and hope indicated that an increase in psychological hardiness would cause increased hope in the university and high school students. In fact, hardiness played a key role in the creation of academic hope in high school and university students. In this regard, it could be stated that persevering individuals are hopeful to confront tensions successfully and efficiently in the event of unpleasant incidents, have the ability to find meaning in distressing experiences, and believe in their own roles as valuable and important individuals. Being perseverant is a sign of psychological health, and those who lack psychological health will get frustrated and depressed in the face of important life events. Actually, psychological hardiness along with hoping for a better life can result in the improvement and enhancement of individuals’ adaptability (4, 40).

The results also showed that all the subscales of patience and all the subscales of academic hope had a positive and significant correlation with the total scores of patience and academic hope. The results of the internal consistency were well reflective of the construct validity and convergent validity of the academic hope scale. Since patience, as an ethical virtue, plays a role in various areas such as coping with psychological pressure through creating a balance between internal and environmental resources, success in education, job and social relations, anger and sexual instinct control, and religiosity, the existence of a correlation between patience and its components and academic hope can well reflect the clarity of the academic hope construct. Furthermore, one of the most important outcomes of patience is the enhancement of hope in individuals. As ethical virtues are accompanied by positive outcomes in an individual’s life, patience, which is a valuable morality, is followed by increased hope in the individual. In fact, patience is amongst the ethical concepts that cause the enforcement of hope in individuals. To justify these expressions, it can be stated that the higher an individual’s scores of patience indicators, the more s/he feels tolerant and satisfied, persistent in his/her affairs without frustration, and having a sort of domination over his or her wishes. Thus, patience may lead to increased hopefulness or a sort of hope and motivation preservation in the individual in any respect. Indeed, patience and toleration of hardships for achieving goals and reaching a higher degree of wishes, and acceptance of the current situation as well as the status wherein an individual is will more likely be accompanied by a set of positive future expectations, lack of doubt about a promising future, and disbelieving in a frustrating future. Individuals with higher tolerance and patience in the face of calamities and difficulties would have less negative expectations about future, the result of which could be increased hopefulness and optimism about future.

The results of assessing the reliability of the academic hope scale in this age group indicated that the scale had an appropriate reliability. Since the majority of instruments developed in the area of hope had assessed the general concept of hope in life, developing an academic hope scale in this research could open new ways to the expansion and performing of research in academic areas and issues related to academic motivation and achievement. Therefore, researchers are suggested to investigate psychometric properties of the academic hope scale in other populations and related to other concepts and variables.

5.2. Second Study

The aim of the second study was to investigate psychometric properties of the academic hope in university students as well. Following the collection and analysis of the data, the confirmatory factor analysis results affirmed the existence of four components in the academic hope scale (hope to gain opportunities, hope to gain life skills, hope in school’s usefulness, and hope to gain competency). Generally, the results of this study indicated that, like the high school form of the academic hope scale, the university student form had favorable validity and reliability and could be employed as a useful instrument for assessing academic hope in university students.

When investigating the convergent and discriminant validity of the academic hope scale for university students according to the study background, this study examined the correlation between the academic hope scale and the conceptual variables in various academic areas. The results of the correlation matrix indicated that hope to gain opportunities, hope in school’s usefulness, hope to gain competency and the total score of academic hope had a positive and significant correlation with academic engagement, admiration emotion, and hope subscale from achievement emotion questionnaire. A negative and significant correlation was also found with all the aforementioned indicators and school burnout. The results provided some evidence implying the convergent and discriminant validity of the academic hope scale with other instruments.

The results of the present study showed a significant correlation between academic well-being areas (academic engagement and school burnout) and academic hope. This finding was consistent with those of the studies (12–14), who showed that hope could have various psychological benefits for individuals. High degrees of hope are associated with well-being and performance, coping strategies and regulating emotional distress. Hope is also a means of life problem prevention (primary and secondary) and is correlated with overall satisfaction with life. Empirical evidence showed that emotions were social structures and personal representations that flexibly played a major role in well-being and quality of university students’ academic lives (41–43). University students who are emotionally and cognitively engaged in learning spend more time and efforts on studying, cope with their academic needs appropriately, and overcome the problems of their schooling period (44). In fact, emotions are factors contributing to academic success in higher education levels (45). Emotions are important for social functions; i.e. they provide the information on social situations. Humans’ essential emotions enable a proper and fast use of responses in line with environmental changes (46). Therefore, it can be pointed out that emotions are social constructs playing roles in facilitation of academic engagement (47). The important role of positive emotions like hope and the process of their impact on academic engagement were confirmed in the theory provided by Pekrun and Linenberg-Garcia (7) as well as previous research (47, 49). Thus, the relationship between academic hope, as a cognitive-emotional construct, and academic engagement and wellbeing confirmed the construct validity of the academic hope scale.

Moreover, it was found out in the investigation of the convergent validity that academic hope scale had a positive and significant correlation with hope emotion subscales in the achievement emotion questionnaire developed by Pekrun et al (35). As previously mentioned, hope has been proposed from various cognitive and emotional perspectives. The cognitive perspective was first expressed by Snyder (2) and, subsequently, the emotional perspective was introduced by Pekrun (6). From the cognitive perspective, hope is a personality trait consisting of a recognition of favorable outcomes that may be possibly achieved in future. According to Snyder (2), hope is not an emotion, but a relatively dynamic motivational-cognitive system. However, in the value-control theory by Pekrun (6), hope is a prospective consequential emotion motivating an individual to make progress. In fact, the previous perspectives dealt with hope as a cognitive-emotional construct, but it was addressed from a cognitive-emotional perspective in the present research, and academic hope was defined as a cognitive-emotional construct. It was said to be an expectation based on which an individual anticipated the occurrence of pleasant events in future. Thus, in the present study, the correlation between academic hope scale’s sub-indicators as well as the total score of academic hope and the hope emotion’s subscales in the questionnaire developed by Pekrun et al (35) suggested that the scale had proper construct validity.

On the other hand, based on the subjective foundations of the control-value theory of achievement emotions by Pekrun and Linenberg-Garcia (7) and previous studies, achievement goals are considered as the main prequels of emotions. Achievement goals influence academic and social emotions. Admiration emotion is one of the social emotions. It is defined as a social other-admiration emotion. An individual with such an emotion usually possesses a series of skills enabling him or her to admire others for their work, characteristics and/or valuable services (38). In fact, individuals with admiration emotion tend to admire more people because they are looking for acquiring social skills in their relations so as to adapt to others. Therefore, considering the academic hope dimensions including hope to gain life skills, they have higher levels of hopefulness and the emotions resulted from it. Furthermore, experiencing positive social emotions such as admiration emotion may increase the students’ concentration of cognitive resources and their focuses and attention to tasks, while experiencing positive emotions such as academic hope will result in greater efforts and use of functional, holistic and flexible cognitive strategies. All these factors may cause the individuals to be more engaged and involved in education in academic environments, enjoy studying, spend much energy on doing their assignments, and, on the other hand, be less influenced by stressful academic factors and experience a lower degree of school burnout. In general, regarding the relationship between the academic hope scale and emotional and motivational areas (Pekrun’s achievement emotions and social admiration emotions) as well as well-being (academic engagement and school burnout), it can be stated that cognitive appraisals influence social achievement goals by recalling challenging evaluations when encountering provoking academic assignment demands, following which social achievement goals will pave the way for facilitation of academic and social achievement emotions, and social and academic emotions will influence academic well-being as well. In the end, it was found out in the second study that the academic hope scale had a very good reliability.

5.3. Conclusions

A new model was presented in this study based on the subjective foundations of Snyder’s perspectives (2), and Pekrun’s control -value theory of achievement emotions (6). The proposed model dealt with academic hope areas more specifically. Unlike previous models that were either cognitive (Snyder’s model, (2)) or emotional (Pekrun’s model, (6)), a cognitive-emotional model for hope was proposed in the present research. Moreover, the advantage of the proposed model to the older ones was the extraction of the indicators (hope to gain opportunities, hope to gain life skills, hope in school’s usefulness and hope to gain competency) based on which one could provide a more precise explanation of hopefulness in academic areas. Since the majority of hope-related instruments constructed so far assessed the general concept of hope in life, developing the academic hope scale in this study, which dealt specifically with academic hope, can provide new paths to expand and conduct research in academic fields and issues related to academic motivation and achievement. Hence, researchers are suggested to study psychometric properties of the academic hope scale in other populations and in respect to other concepts and variables. In the end, the academic hope scale can pave the way for novel studies in hope-specific areas. Furthermore, considering favorable psychometric properties of this scale, it can also be used for counseling and clinical applications.

Author contributions FK and SK designed the study; SK contributed to data collection and conducted the statistical analysis and SK and FK analysis and interpretation of data: SK drafting of the manuscript: FK and MMK critical revision of the manuscript for important intellectual content: SK wrote the first draft of the manuscript. All authors read and approved the contents of the final manuscript.

Funding/Support The authors did not receive any financial support for the publication of this study.

Data availability The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Conflict of Interest The authors declare that they have no conflict of interest.

Ethical Statement All procedures performed in studies involving human participants were in accordance with the ethical standards of APA researches.

Consent Statement Informed consent was obtained from the educators and parents/guardians of participating students. The students gave their assent for inclusion.

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Development and Validation of the Academic Hope Scale (AcHS) for Students

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Version 1

Abstract

Figures

Introduction

Objectives

First Study

3. Methods

3.1. Population, Participants and Sampling

3.2. Instruments

4. Results

4.1. Validity of Academic Hope Scale (AcHS)

4.2. Reliability of Academic Hope Scale

Second Study

3. Method

3.1. Population, Participants and Sampling

3.2. Instruments

Results

4.1. Construct Validity via Factor Analysis

4.2. Correlation of academic hope scale with other tests

4.3. Reliability of academic hope scale via internal consistency

Discussion

5.1. First Study

5.2. Second Study

5.3. Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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Version 1