Development and initial validation of the life skills ability scale for higher education students

ABSTRACT This research developed a scale to assess the following life skills in higher education students: teamwork, goal setting, time management, emotional skills, interpersonal communication, social skills, leadership, and problem solving and decision making. Study 1 adapted an existing scale for the purposes of this research and provided evidence for the factorial validity of the new scale with 445 students. Study 2 included 423 students and supported the predictive validity of the scale in relation to students’ psychological well-being, academic self-efficacy/performance, and health-related quality of life. Study 3 provided evidence for the test-retest reliability of the scale with 49 students. All three studies supported the internal consistency reliability of the scale. Combined, these studies suggest that the scale is a valid and reliable measure that researchers, policymakers and educators could use to assess and potentially enhance higher education students’ life skills. Future research directions and uses of the scale are discussed.


Introduction
Life skills are defined as the 'skills or abilities individuals need in order to achieve success in life' (Murray, Clermont, and Binkley 2005, 51). Examples of life skills include teamwork, communication, time management, and leadership skills. Previously, terms such as 'core', 'key', 'soft', 'generic', 'transferable', 'employability' and 'life' skills have been used interchangeably within the research literature (Atkins 1999;Dacre Pool and Sewell 2007;Robles 2012;Tsitskari et al. 2017). In particular, the term 'employability skills' has been used extensively in the research literature to refer to 'personal, social, and transferable skills seen as relevant to all jobs' (Blades, Fauth, and Gibb 2012, 3). However, we use the term 'life skills' as skills like teamwork, goal setting, leadership, and social skills are used in education, sports, extracurricular activities, and social relationshipsalong with being used within employment. Highlighting this point, a report published by the Higher Education Academy (Artess, Hooley, and Mellors-Bourne 2017) proposed that such skills have relevance for education, family life, citizenship, and the workplace. Similarly, research by Steptoe and Wardle (2017) showed that life skills play a role in promoting young people's health, educational achievement and occupational success. The importance of life skills is further highlighted by the Bologna Declaration (1999) and its accompanying policies, processes and principles, which promote the development of skills which students require for European citizenship and employment (Yerevan Communiqué 2015). This illustrates that political and economic leaders are particularly focused on improving the skills of future workers to promote economic prosperity (Wolf, Zahner, and Benjamin 2015). In fact, it would be fair to say that one of the main aims of higher education is to equip students with the skills required for the workplace (Britton et al. 2017).
But what specific life skills do higher education students need for the workplace? Through her review of the research literature, Jackson (2010) highlighted the importance of the following skills across industries and countries: problem solving, decision management, oral communication, team-working, interpersonal skills, leadership, and emotional intelligence. Research specific to different industries or degree programmes has also highlighted the importance of such skills. For instance, Azevedo, Apfelthaler, and Hurst (2012) surveyed 900 business graduates and employers in four European countries and highlighted that teamwork, leadership, and communication are key skills required within business. Within the sports sector, Baker et al. (2017) surveyed 1,132 sports graduates and 327 employers across six European countries and identified teamwork, communication, social skills, leadership, and problem solving as crucial skills for sports graduates.
Despite research suggesting that graduates require such skills, many employers believe that today's graduates are lacking in these skills. For example, the British Chamber of Commerce (2014) suggested that 54% of businesses consider graduates to lack work-appropriate skills. Other researchers have suggested that degree programmes may not be equipping students with the skills needed within employment (Cranmer 2006) and raises the question of what can be done to promote the development of students' life skills. In this regard, the Bologna Declaration (1999)which has greatly shaped higher education policies in Europeproposed that we require university-wide practices for embedding, developing, assessing and reporting non-technical competencies (Jackson and Chapman 2012). Such a proposition aligns with competence or skills-based higher education (Bergsmann et al. 2018), which entails the student developing certain skills during their degree programme. Two approaches that Cranmer (2006) suggested for skills development are to embed skills within the curriculum or ensure they are taught parallel to the curriculumwith the latter seen as the best approach. Other researchers have suggested that key aspects of a degree programme which help students develop their life skills are work experience and volunteering opportunities (Baker et al. 2017;Dacre Pool and Sewell 2007).
Despite life skills being important within higher education, few valid and reliable measures exist to track students' life skills. Although, it must be noted that some recent efforts have been made to start assessing higher education students' skills and competencies (for an overview, see Zlatkin-Troitschanskaia, Pant, and Coates 2016). Nonetheless, several researchers (e.g. Blades, Fauth, and Gibb 2012;Riebe and Jackson 2014;Zlatkin-Troitschanskaia, Pant, and Coates 2016) have suggested that new measures are required to assess students' skills and competencies. This is particularly the case as previous measurement efforts have focused primarily on students' knowledge and cognitive skills (Zlatkin-Troitschanskaia, Shavelson, and Kuhn 2015) as opposed to their broader life skills. Importantly, developing a life skills measure would allow researchers to investigate whether students are developing life skills during their degree programme and allow for theory-based research concerned with the antecedents and consequences of life skills development in higher education. Porter (2013) has further recommended that measures be used to assess students' skills at the beginning and throughout their degree programme, which would allow educators to investigate the effectiveness of degree programmes in developing students' life skills. Finally, a new measure to assess students' life skills would help when investigating if elements of a degree programme/curriculum (e.g. teaching content, assessments, and work placements) promote students' life skills development.
Heeding the call for new life skills measures to be developed, the current research focused on developing a scale to assess the following life skills in higher education students: teamwork, goal setting, time management, emotional skills, interpersonal communication, social skills, leadership, and problem solving and decision making. In line with the guidance provided by The Standards for Educational and Psychological Testing (AERA, APA, and NCME 2014), three studies were conducted to develop and provide validity and reliability evidence for this new scale.

Study 1
The aim of this study was to develop a scale to measure students' life skills ability. This involved adapting an existing measure for use as a life skills ability scale and testing the factorial validity and internal consistency reliability of the measure with a sample of higher education students.

Participants
The sample included 445 students from three UK universities (M age = 21.77, SD = 5.49, age range = 17-50 years). Both male (n = 227) and female (n = 216) students were included (two students did not indicate their gender). Students were predominantly from undergraduate degree programmes in sports (n = 193), psychology (n = 153), and computer game design (n = 83). The following year groups were included: foundation year (n = 22), first year (n = 165), second year (n = 208), third year (n = 41), and year one of an MSc (n = 5).

Life skills ability scale (LSAS)
In this study, we adapted the Life Skills Scale for Sport (LSSS; Cronin and Allen 2017) to develop a Life Skills Ability Scale (LSAS) for higher education students. This new scale (see Appendix A of the supplementary materials for the complete scale) assesses students' teamwork, goal setting, time management, emotional skills, interpersonal communication, social skills, leadership, and problem solving and decision making abilities. These life skills are commonly cited as skills which young people use in a broad range of settings including sports, education, and the workplace (Artess, Hooley, and Mellors-Bourne 2017; Cronin and Allen 2017; Jackson 2010). The definitions and components of the life skills are included in Table A of the supplementary materials. The LSSS was adapted by firstly changing the general instructions to fit with the assessment of students' life skills abilities. The item stem was also changed from 'This sport has taught me to … ' to 'I am able to … ' Finally, the original response format was changed from 1 (not at all) to 5 (very much) to 1 (strongly disagree) to 5 (strongly agree). For the most part, the 43 items in the LSSS were retained. However, fours items were amended to better fit with the measurement of students' life skills (e.g. 'set goals for practice' was changed to 'set goals for my activities'). Examples of items which comprised the new scale included: teamwork (7 items; 'work well within a team/ group'), goal setting (7 items; 'set specific goals'), time management (4 items; 'manage my time well'), emotional skills (4 items; 'notice how I feel'), interpersonal communication (4 items; 'speak clearly to others'), social skills (5 items; 'interact in various social settings'), leadership (8 items; 'be a good role model for others'), and problem solving and decision making (4 items; 'think carefully about a problem').

Procedures
The 43-item LSAS was completed by students prior to a teaching session at mid-semester. Before the data collection, ethical approval was granted by the universities ethics committees and informed consent was obtained from all participants. Students completed the scale after the researcher gave an introductory statement which explained the purpose of the study, that there were no right or wrong answers, and that all information provided was confidential. The scale took approximately 5-10 min to complete.

Data analyses
To assess the factorial validity of the scale, confirmatory factor analysis (CFA), exploratory structural equation modelling (ESEM) and bifactor analyses employing maximum likelihood estimation was conducted using Mplus (Version 7.4; Muthén andMuthén 1998-2015). The following models were tested: an eight-factor CFA model, a second-order CFA model, a first-order CFA model, a bifactor CFA model, an ESEM model, a higher-order ESEM model (H-ESEM), and a bifactor ESEM model (B-ESEM). A visual depiction of each of these models can be seen in Appendix B of the supplementary materials. For a complete description of these models and the procedures used to test them, see Cronin and Allen (2017). The following fit indices were used to assess model fit: chi-square statistic divided by degrees of freedom (χ²/df ), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and the Tucker Lewis Index (TLI). A χ²/df of less than 3.0 was indicative of adequate fit (Tabachnick and Fidell 2013). In line with Marsh, Hau, and Wen's (2004) recommendation, an RMSEA value of less than .08 or .05 represented a reasonable or close fit to the data respectively; whereas, CFI and TLI values greater than .90 or .95 indicated acceptable and excellent fit respectively. Competing models were also compared using procedures outlined by Morin, Arens, and Marsh (2016). Similar model fit is evident when changes are <.015 for the RMSEA, <.01 for the CFI, and <.01 for the TLI. Lower values for the Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), and sample size adjusted BIC (ABIC) are also indicative of better model fit (Appleton et al. 2016). Along with examining fit indices and information criteria, Morin, Arens, and Marsh (2016) suggested that researchers should examine the parameter estimates of the solutions to guide the selection of the best model.

Results
During the analyses, seven competing models were examined. The fit indices and information criteria for these models are contained in Table 1 and the factor loadings for the models are contained in Tables B, C, and D of the supplementary materials. When tested, the B-ESEM model provided the best representation of the data, as it displayed the best fit indices and lowest AIC and ABIC values when compared to all other models. With the B-ESEM model (see Table D), all items loaded significantly onto the general life skills factor (M factor loading = .49, range = .25-.64) which suggests that a general life skills factor is evident within the data and it would be appropriate to calculate a total life skills ability score. In the B-ESEM model, 41 items also loaded onto their specific life skills factor (M factor loading = .44, range = -.20-.76). Only two items failed to load onto their specific life skills factor (i.e. one teamwork item and one interpersonal communication item), with two of these items having higher cross-loadings on other specific factors. It is important to note that a small number of non-loading and cross-loading items are often seen in studies using B-ESEM models (e.g. Fadda et al. 2017;Morin, Arens, and Marsh 2016;Sánchez-Oliva et al. 2017). This is due to the more flexible statistical approach being used (i.e. items are free to load onto multiple factors) and the fact that individual items are never a 'pure' indicator of a construct (Morin, Arens, and Marsh 2016).
Lastly, the internal consistency reliability of each subscale was tested (see Table 2). For seven of the eight subscales, alpha coefficients were above the .70 criterion suggested by Nunnally and Bernstein (1994) to indicate adequate reliability. Only the emotional skills subscale had an alpha coefficient of .66, which was marginally below the .70 criteria. The mean scores on the 1-5 response scale for students' perceived life skills abilities ranged from 3.45 for time management to 4.16 for teamwork (see Table 2). This indicated that students perceived their life skills abilities to be moderately high.

Study 2
The main aim of this study was to assess the predictive validity of the LSAS. In this regard, past research has suggested that individual life skillsalong with total life skillsshould be positively related to other important outcomes in young people. For example, emotional skills (Nelis et al. 2011), social skills (Segrin and Taylor 2007), time management (Chang and Nguyen 2011), and problem solving (D'Zurilla and Nezu 2010) have all been positively associated with young peoples' psychological well-being. Goal setting (Locke and Latham 2002) and time management (Broadbent and Poon 2015) have been positively related to students' academic achievement. Emotional skills (Nelis et al. 2011) and time management (Claessens et al. 2007) have been positively associated with young peoples' physical functioning and health. Social skills (Smith and Betz 2000) and emotional skills (Nelis et al. 2011) have been positively related to social functioning. Goal setting (Brunstein, Schultheiss, and Grässman 1998) and social skills (Smith and Betz 2000) and have been positively associated with emotional functioning. Finally, teamwork, communication, leadership, and problem solving and decision making have been positively related to students' work functioning (Waldman and Korbar 2004). Regarding total life skills, Benson (2006) proposed that the more strengths or life skills a young person possesses, the better off they will be on a range of positive outcomeswhich has been termed the 'pile-up' effect. Scales et al.'s (2016) review of the youth development literature supported this idea, with the total number of strengths a young person possesses being positively associated with psychological, academic, and behavioural outcomes. Based on the above research, we predicted that some of the individual life skills and total life skills would be positively related to students' psychological well-being, academic self-efficacy, predicted academic performance, and health-related quality of life (physical, social, emotional, and work/school functioning). It was difficult to hypothesize which of our eight life skills would be positively associated with our seven outcome variables as past research has only explored a limited number of these potential relationships.

Life skills ability
The 43-item LSAS was used to assess students' life skills abilities. This scale was described in Study 1 and can be seen in Appendix A of the supplementary materials.

Psychological well-being
Psychological well-being was assessed using the 8-item Flourishing Scale (Diener et al. 2010). This scale asks participants to respond to statements related to their psychological well-being. Example items include: 'I lead a purposeful and meaningful life' and 'I am optimistic about the future'. Participants respond to items on a 1 (strongly disagree) to 7 (strongly agree) scale. Past research has supported the validity and internal consistency reliability of the scale with university students (Diener et al. 2010). With the current sample, the internal consistency reliability of the scale was supported (α = .86).

Academic self-efficacy and performance
Academic self-efficacy was assessed using the 8-item Academic Self-Efficacy Scale (Chemers, Hu, and Garcia 2001). This scale asks participants to disagree or agree with statements that assess their academic self-efficacy. Example items include: 'I am a very good student' and 'I am very capable of succeeding at university'. Participants respond to items on a 1 (very untrue) to 7 (very true) scale. Past research has supported the content validity and internal consistency reliability of this measure with university students (Chemers, Hu, and Garcia 2001). With the present sample, the internal consistency reliability of the scale was supported (α = .89). Along with rating their academic self-efficacy, the students were asked to predict their academic performance by responding to the following item: 'Please indicate (in percentage terms) what you believe your overall average grade will be at the end of the current academic year?'

Health-related quality of life
Health-related quality of life was assessed using the 23-item Paediatrics Quality of Life Inventory -Young Adult Version (Varni and Limbers 2009). This inventory assesses quality of life in four domains: physical functioning, emotional functioning, social functioning, and work/school functioning. Example items include: physical functioning ('It is hard for me to run'), emotional functioning ('I feel sad or blue'), social functioning ('I have trouble getting along with other adults'), and work/school functioning ('I have trouble keeping up with my work or studies'). Participants respond to items on a scale ranging from 1 (never) to 5 (almost always). Research has provided evidence for the reliability and validity of this measure with students (Varni and Limbers 2009). With the current sample, the internal consistency reliability of each subscale was supported (α range = .75-.80).

Procedures
The same procedures regarding ethical approval, informed consent, participant instructions, and data collection as Study 1 were adopted in the present study. The survey took approximately 15-20 min to complete.

Data analyses
As validity and reliability are ongoing processes which should be continually assessed (DeVellis 2011), the same procedures used to analyse the factorial validity and internal consistency reliability of the scale in Study 1 were replicated in this study. To assess predictive validity, Pearson's product moment correlations were calculated to investigate the relationships between the LSAS subscales and students' psychological well-being, academic self-efficacy, predicted academic performance, and health-related quality of life.

Factorial validity and reliability analyses
The fit indices and information criteria for the seven models examined are contained in Table 1 and the factors loadings for the models are included in Tables E, F, and G of the supplementary materials.
As can be seen in Table 1, the B-ESEM model provided a better fit than the other models as evidenced by improved fit indices and lower AIC and ABIC values. With the B-ESEM model (see Table G of the supplementary materials), all items loaded significantly onto the general life skills factor (M factor loading = .45, range = .29-.65). Like Study 1, this indicated the presence of a welldefined general life skills factorjustifying the calculation of a total life skills score. In the B-ESEM model, 36 items also loaded onto their specific life skills factor (M factor loading = .46, range = -.18-.78). However, four items had higher cross-loadings on other specific factors as compared to their own specific factor (i.e. one teamwork, one social skills, and two leadership items) and seven items failed to load onto their specific factor (i.e. one interpersonal communication, one social skills, and five leadership items). Again, some non-loading and cross-loading items are often seen in B-ESEM models (e.g. Fadda et al. 2017;Sánchez-Oliva et al. 2017) due to the more flexible statistical approach being used and the fact that items are never a 'pure' indicator of a construct (Morin, Arens, and Marsh 2016). The internal consistency reliability for each subscale was also tested in this study (see Table 2). For all eight life skills, the internal consistency reliability of the subscales was supported. From Table  2, we can see that the mean scores for students' perceived life skills abilities were moderately high: teamwork (4.12), social skills (4.10), interpersonal communication (4.04), leadership (3.94), problem solving and decision making (3.85), goal setting (3.76), emotional skills (3.71), and time management (3.40).

Correlations
The correlations between the life skills and the dependent variables can be seen in Table 3. The correlations between all of the life skills and participants' psychological well-being were significant and positive (r range = .32-.62). The relationships between all of the life skills and academic self-efficacy were also significant and positive (r range = .23-.54). In contrast, only goal setting, time management, leadership, and total life skills were positively associated with predicted academic grade (r range = .17-.28). Time management, emotional skills, leadership, and total life skills were related to students' physical functioning (r range = .10-.14). All life skills, except for leadership, were positively associated with students' emotional functioning (r range = .11-.26). With the exception of goal setting/problem solving and decision making, all life skills were positively related to students' social functioning (r range = .13-.31). Lastly, the correlations between all of the life skills and students' work/school functioning were significant and positive (r range = .17-.38). In sum, these findings provided evidence for the predictive validity of the LSAS by showing that the eight life skillsalong with total life skillswere positively associated with students' psychological well-being, academic selfefficacy, predicted academic grade, physical functioning, emotional functioning, social functioning, and school/work functioning. .17*** .23*** .38*** .20*** .24*** .21*** .22*** .25*** .36*** Note: N = 423. Problem solving = Problem solving & decision making. *p < .05, **p < .01, ***p < .001.

Study 3test-retest reliability
A second form of reliability to be examined during the scale validation process was test-retest reliability. Essentially, test-retest reliability is a method used to assess how constant scores remain from one occasion to another (DeVellis 2011). Thus, the aim of this study was to assess the testretest reliability of the LSAS using a one-week test-retest analysis. A one-week timeframe was chosen as students' life skills were unlikely to change over this short time and past test-retest reliability studies with university students have used this timeframe (e.g. Lewis, Cruise, and McGuckin 2005).

Participants
The sample included 49 UK university students (M age = 21.53, SD = 4.17, age range = 18-39) who completed the LSAS on two occasions. The sample included more males (n = 34) than females (n = 15). Students were from undergraduate degree programmes in sports therapy (n = 28), sport and exercise science (n = 11), and sport science and coaching (n = 10). Using Bonett's (2002) procedures for calculating the required sample size for estimating intraclass correlation coefficients (ICCs) in reliability studies, we found that our sample size was above the minimum sample size of 43 required to calculate ICCs in the present study.

Measures and procedures
The LSAS was used to measure students' life skills abilities after teaching sessions which were one week apart. The LSAS was described in Study 1 and can be seen in Appendix A of the supplementary materials. The same procedures regarding ethical approval, informed consent, participant instructions, and data collection as Study 1 were adopted in this study. The scale took 5-10 min to complete on each occasion.

Data analysis
ICCs were used to assess test-retest reliability. ICCs are a measure of reliability that can range from 0 (indicating no reliability) to 1 (indicating perfect reliability), with values above .70 providing evidence of adequate reliability (Mitchell and Jolley 2001).

Results
As can be seen in Table 2, the ICCs in this study were all above the .70 criterion needed to demonstrate adequate test-retest reliability (range = .77 to .92). From Table 2, we can also see that students perceived their life skills abilities to be moderately high.

Overall discussion
The purpose of the present research was to develop a scale to assess higher education students' perceptions of their life skills abilities. During this research, we developed and provided validity and reliability evidence for the 43-item LSAS which measures students' teamwork, goal setting, time management, emotional skills, interpersonal communication, social skills, leadership, and problem solving and decision making skills. Specifically, across three studies we provided evidence for the factorial validity, predictive validity, test-retest reliability and internal consistency reliability of the LSAS. This research is an important development in the assessment of students' life skills as ensuring scales are valid and reliable is the first stage of the research process (Schutz 1994). Our findings suggest that researchers using the LSAS can be confident in the accuracy of the scores they obtain, the relationships they find with other variables, their interpretation of such relationships, and the implications for both educators and students. Additionally, the scale will be an important tool for higher education practitioners as the life skills it measures are cited as skills young people require within the workforce and beyond (e.g. Artess, Hooley, and Mellors-Bourne 2017;Azevedo, Apfelthaler, and Hurst 2012;Baker et al. 2017;Jackson 2010;Steptoe and Wardle 2017), but few robust measures exist to assess them (Riebe and Jackson 2014).
From a theoretical standpoint, the LSAS will allow researchers to test various theories that may explain the processes by which young people develop their life skills. For example, self-determination theory (SDT; Ryan and Deci 2017) proposes that the following causal sequence could be investigated in relation to students' life skills development: instructor autonomy supportstudents' basic need satisfactionself-determined motivationlife skills ability. Using the LSAS and self-determination theory, researchers can begin to examine the social/environmental determinants and underlying psychological mechanisms of life skills development in higher education. Through theory testing, researchers may be able to provide educators and policymakers with theory-based evidence, explanations, and guidance on how they can develop students' life skills.
Within the present research, the three studies indicated that students perceived their life skills abilities to be moderately high. Interestingly, the mean scores for the life skills and the ordering of the life skills from highest to lowest was similar across Studies 1 and 2 (i.e. the large-scale data collections). These studies highlighted that the students scored highest on teamwork, interpersonal communication, social skills, and problem solving and decision making; whereas, they scored lowest on time management, emotional skills, goal setting, and leadership. Building on these cross-sectional findings, future research could track students' life skills abilities to investigate changes that may occur over time, why and how these changes may occur, and to assess the long-term impact of life skills obtained during a degree programme. Based on such findings, higher education institutions could seek to improve their policies/curriculums to promote students' life skills. Specifically, the teaching, learning, and assessment strategies within degree programmes could focus on helping students to develop particular life skills. For example, group work within seminar sessions may be used to enhance students' teamwork skills; whereas, individual presentation assessments may promote their communication skills. Future studies could also investigate the impact that co-curricular activities (e.g. work experience, volunteering, and study abroad programmes) and extra-curricular activities (e.g. club or student council membership) have on students' life skills. Another area of research would involve using the LSAS to examine the efficacy of existing programmes designed to teach students life skills. The learning/career services departments of many universities conduct programmes aimed at teaching students' life skills such as goal setting and time management, and using the LSAS, the success of such programmes ought to be examined. Lastly, given the popularity of online and hybrid courses within the United States (Chingos et al. 2017), it would be interesting to assess students' life skills development during such courses. Overall, greater knowledge of students' life skills abilities and how to enhance them would be particularly important given the role that life skills play in promoting young peoples' educational and occupational successalong with their health (Steptoe and Wardle 2017).
Our findings from Study 2 clearly highlighted that individual life skills and total life skills are positively associated with educational and health outcomes such as students' psychological well-being, academic self-efficacy and performance, and health-related quality of life. This is a significant finding as it illustrates the broader importance of life skills in predicting other positive outcomes in students' lives. Specifically, our results highlight that the eight life skills measured by the LSAS could be the focus of future intervention studies aimed at enhancing students' academic performance, health and well-being. For instance, given the strong positive relationship between students' total life skills and their psychological well-being, future intervention studies teaching students the eight life skills may help to enhance their psychological well-being. Research focused on enhancing students' health and well-being through the development of their life skills is particularly important given that university is often the first time that young people take responsibility for their own health and well-being (Ridner et al. 2016). Moreover, given the growing levels of psychological distress reported in university students (Bewick et al. 2010), studies assessing how certain life skills may impact upon students' mental health are warranted. In terms of educational outcomes, the growing interest in how non-cognitive or psychosocial skills can affect students' academic performance (Olivera-Aguilar, Rikoon, and Robbins 2017) suggests that future research should assess how particular life skills may impact students' performance on different types of assessments. For example, do students with better problem solving skills perform better on case study assessments (e.g. a client case study in psychology); whereas, students with better leadership skills may perform better on practical assessments (e.g. a coaching practical in sport science)? Another question that remains unanswered within the literature is how life skills learned within higher education are transferred and used in other settings. In this regard, Jackson and Chapman (2012) emphasized that it can be challenging for skills learned in university to be transferred to the workplace. Future studies incorporating the ideas of 'near' and 'far' transfer of skills (Bennett, Dunne, and Carré 2000) along with the notion that life skills can be 'explicitly' or 'implicitly' developed and transferred (Bean et al. 2018)could shed light on how life skills can be developed in students and transferred to other aspects of their lives.

Limitations and future directions
Addressing the limitations of the current research (i.e. a focus on UK university students and Studies 2-3 only including sports degree students), future studies should examine the LSAS in other countries/cultures and test the psychometric properties of the scale across different degree programmes. Given that the emotional skills subscales displayed a reliability coefficient marginally less than the .70 criteria (Nunnally and Bernstein 1994) in two of four data collections, it is important to re-assess the internal consistency reliability of this subscale with another sample. Additionally, given that some cross-loading and non-loading items were evident across our B-ESEM models in Studies 1-2, it would be important to re-assess these items during future studies. Regarding our predictive validity assessment in Study 2, future research could take a more fine-grained or theory-driven approach to exploring the relationships between the life skills and specific outcome variables. For instance, research could further assess if time management and goal setting are related to predicted academic grades through the mediator of academic self-efficacy. In relation to Study 3, future studies should assess the test-retest reliability of the LSAS over different periods of time (e.g. 2-6 weeks) and with larger sample sizes. Another limitation of the present research is that the LSAS relies on participants' perceptions of their life skills abilities. With any self-report measure, there are always concerns with social desirability and the accuracy of responses (Zilvinskis, Masseria, and Pike 2017;Zlatkin-Troitschanskaia, Shavelson, and Kuhn 2015). Thus, we would encourage future studies to gain others' perspectives on students' life skills abilities (e.g. teaching staff, work experience supervisors, graduate employers) to assess the accuracy of students' ratings. This is especially the case as higher achieving students tend to underestimate their abilities, lower achievers tend to overestimate their abilities (Leach 2012), and students in general overrate their performance in comparison to teaching staff (Britton et al. 2017).

Conclusion
The present research provided initial evidence for the validity and reliability of the LSAS which can be used to thoroughly assess students' life skills abilities. Researchers can use the LSAS to test theories investigating the mechanisms that lead to students' life skills development in higher education. The transfer of life skills to other settings and the impact of life skills on students' academic performance, health and well-being could also be assessed using the scale. Moreover, teaching and learning services staff may use the scale to examine whether their efforts to develop certain life skills in students are effective or not. Ultimately, it is hoped that the LSAS proves a useful tool for researchers, policymakers, and educators interested in the promotion of life skills in higher education.