Conceptualizing non-cognitive attributes, entrepreneurship t

刊名: International Journal of Technology and Design Education 作者:Evans Mwasiaji1  · Shadrack Mambo2 · Godfrey S. Mse3 · John Okumu4 来源:International Journal of Technology and Design Education 发布时间:2021-07-07 10:25
Keywords Non-cognitive attributes Entrepreneurship training Pedagogical competencies STEM education outcome Introduction Though humanities are important in teaching learners to reason about being human, a strong identity in Science, Technol
Keywords Non-cognitive attributes · Entrepreneurship training · Pedagogical competencies · STEM education outcome
Though humanities are important in teaching learners to reason about being human, a strong identity in Science, Technology, Engineering and Mathematics (STEM) fields has been associated with improved economic performance (Burnett & Jayaram, 2012; The American Institute Report, 2015). With active industrial initiatives, many countries take positive outcomes in STEM education to constitute a critical part of skills development process that is essential in inducing responsiveness to fluctuations in economic conditions.
According to Ostler (2012), STEM education goes beyond mere transfer of knowledge, but also empowers the next generation of innovators required to succeed in the current
* Evans Mwasiaji 1 Department of Business Administration, Kenyatta University, P.O. Box 43844, Nairobi City GPO 00100, Kenya 2 Department of Electrical & Electronic Engineering, Kenyatta University, Nairobi City, Kenya 3 Department of Education Management. Policy & Curriculum Studies, K.U, Nairobi City, Kenya 4 Department of Physics, Kenyatta University, Nairobi City, Kenya
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dynamic, globalized and competitive work environment. This observation is anchored on empirical evidence which show that STEM education enables students gain skills includ- ing the ability to think critically, solve complex problems, and drive advancements in sci- ence and technology in the work place, community and the global arena (Margot & Kettler, 2019; Voogt & Roblin, 2012; Williams, 2011). With unemployment reaching new heights especially in less developed countries due to difficult economic conditions, effective learn- ing outcomes in STEM education is considered a counteracting force in resolving inad- equacy in supply of skills required by employers to match progress in information and communication technology (Burnett & Jayaram, 2012). STEM education may be consid- ered useful in creating productive employment, enhancing international competitiveness and generating value added income towards the attempt to reach the poorest of the poor (Voogt & Roblin, 2012; Williams, 2011). Many countries have consequently invested in STEM education so as to ultimately improve the standards of living for the citizenry. This is premised on the argument that manufacturing and services industries which are critical for industrialization and economic diversification require positive outcomes in STEM edu- cation (Wan et al., 2016). Unfortunately, STEM education has had a high attrition rate for students and inadequate gender balance (Makarova, Aeschlimann & Herzog, 2019; Archer & MacRae, 1991; Cundiff et al., 2013).
In an attempt to understand the cause of high attrition of students, improve education outcomes and address the shortage of STEM workers, research energy has been directed towards establishing a correlation with non-cognitive attributes or soft skills such as extra- version, agreeableness, conscientiousness, neuroticism and openness that may not neces- sarily be based on conscious intellectual activity (Kautz et. al., 2014; Makarova, Aeschli- mann & Herzog, 2019). These studies are part of the synergy to development antidotes to patch leakage points along the STEM education pipeline (Barrett, 2014; Poropat, 2009).
For instance, Burrus  et al. (2011a) study established that non-cognitive attributes influence students’ academic achievement and educational aspirations. This finding is in tandem with other studies which reported that children and adolescents’ levels of self-efficacy, self-con- cept and self-confidence predict their mathematics, science and reading scores (Stankov & Lee, 2014). Similarly, meta-analyses of relevant studies revealed that non-cognitive attrib- utes such as conscientiousness, self-efficacy, achievement motivation, and test anxiety are some of the predictors of academic achievement and attrition rates of students (Robbins et al., 2004; Barrett, 2014; Stankov & Lee, 2014). Though non-cognitive attributes are important predictors of academic achievement and behavioral adjustment from early child- hood, they are not by themselves sufficient to guarantee positive outcomes in STEM educa- tion (Abe, 2005). There is also educators and their level of competency in pedagogy which has been shown to influence knowledge and skill transfer to learners during STEM classes.
According to VanTassel-Baska and Little (2011), Fisher et. al. (2013) and Freeman et al. (2014), pedagogy being the adopted content delivery approach during the interaction between teachers and students in the learning arena is a key variable in determining STEM education learning outcomes. Having a well-thought-out pedagogy based on the entry behaviour of learners can improve the quality of teaching by helping students gain a deeper understanding of the subject area (Bruce-Davis et al., 2014; McMullin & Reeve, 2014).
However, how to pedagogically integrate the disciplines in STEM education to optimize learning outcomes continues to be a main point of debate in academic discourse. Some studies have in this context recommended either or a combination of the five pedagogical frameworks including constructivism, Collaborative, Inquiry-Based, Integrative or Reflec- tive approaches in guiding students to examine problems from all angles (Trapmann et. al., 2007; Bagiati & Evangelou, 2015; Prince, 2004). Since teaching is usually by means
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of rules, abstractions and verbal descriptions, the adopted instruction method should be contextualized by drawing concepts from culturally meaningful environment (Gomez & Albrecht, 2013; Lesseig et al., 2016). Irrespective of the methodology employed, it should encourage active learning by engaging learners so as to result in deeper conceptual under- standing, retention of knowledge, student success and persistence in STEM education (Freeman, 2014; Prince, 2004; Trapmann et. al., 2007). Moreover, there is need to integrate entrepreneurship skill training in the curriculum for educators who facilitate STEM ses- sions in tertiary institutions of learning. This is because graduates in STEM education are likely not to fully benefit from their innovations unless they are equipped with innovative skills and mind-sets (McLeod, 2019; Elliott et. al., 2000; Nadelson et. al., 2013). Hence the need for an integrated theoretical model that takes into account the mediating and moder- ating effect of entrepreneurship skills and pedagogical competencies, on the relationship between non-cognitive attributes and STEM education learning outcomes.
Problem statement
The role of STEM education especially in the context of its contribution to sustained global economic growth and development has been hailed as an avenue towards improving the social and economic welfare of mankind (Lesseig et. al., 2016). This acknowledgement is anchored on conclusions of diverse studies based on their constructs, operationalization and methods employed, which reported that improvements in quality of life for humanity is realised to a large extent through research, inventions, new product development and commercialization of inventions (Freeman et. al., 2014). Though several researches are in agreement on the need for strong identity in science-based subjects, there is however diverse propositions on dimensions of the subject matter including how best to optimize positive STEM education learning outcomes. Arising from an intensive review of litera- ture, this study therefore identified issues that require data sets to progress knowledge use- ful for student mentorship and policy formulation to promote STEM education outcomes.
For instance, despite numerous studies such as Bagiati and Evangelou (2015), Lesseig et. al., (2016), McMullin and Reeve (2014) and Bruce-Davis et. al., (2014) explaining the importance of having a strong presence in STEM fields, there still exists a debate about the link between non-cognitive personal attributes and education outcomes (Barrett, 2014; Kautz et. al., 2014). Some studies have in addition argued that though non-cognitive attrib- utes are important predictors of academic achievement and change in behavior from child- hood, such traits are not by themselves adequate in guaranteeing positive outcomes by students pursuing STEM education (Abe, 2005; Gomez & Albrecht, 2013; Prince, 2004; Stankov & Lee, 2014).
Studies have also reported that content delivery approach is essential in helping learn- ers gain a deeper understanding of fundamental concepts conveyed in educational materi- als (Burnett & Jayaram, 2012), though how to pedagogically integrate subjects in STEM education to optimize learning outcomes remains contentious among researchers (Hooker, 2017; The American Institute Report, 2015). There is also a debate about STEM educa- tors and their competency in pedagogy (Barrett, 2014). Many studies have consequently identified the importance of STEM pedagogy training especially in institutions of higher learning (Gomez & Albrecht, 2013; Hooker, 2017). While academic staff in Universities may have a good background and deep understanding in their respective areas of speciali- zation, there are cases where professors have been found to possess limited skills in STEM
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pedagogy (Kautz et. at., 2014) hence impacting negatively on students’ opportunity to suc- ceed in their current and future academic endeavors (Burnett & Jayaram, 2012) and subse- quent performance in the workplace (Li, 2014; Margot & Kettler, 2019; Minichiello et al., 2018). Moreover, empirical data has shown that having knowledge of an academic subject is no longer sufficient for a new graduate (Burnett & Jayaram, 2012; Hooker, 2017). STEM education graduates are for instance unlikely to fully benefit from their innovations unless they are equipped with entrepreneurship skills and mind-sets (Sanders, 2012) to enable them develop ability to recognize commercial opportunities and skills to act on them (Aus- tin, Stevenson & Wei–Skillern, 2006). Entrepreneurship training would also be useful in helping learners gain skills in creativity, innovation and collaboration with others for pur- poses of benefiting from synergy (Block & Stumpf, 1992). Entrepreneurship students are also taught how to develop self-confidence, opportunity recognition, concept commerciali- zation, managing resources and initiating a business venture so as to create value for self and humanity by managing successful business ventures.
Further, research discussions have pursued the construct of non-cognitive attributes separately from that of entrepreneurship skills and pedagogical competencies, (Spark- man et al., 2012; Kautz et. al, 2014; Abe, 2005; Stankov & Lee, 2014), notwithstanding the inferred indications that the three variables can be adapted in an integrated model to enhance STEM education outcomes. The diverse study results and propositions above coupled with inadequate empirical data does not give confidence to researchers to arrive at concrete conclusions on the correlation between non-cognitive attributes and facets of STEM education outcomes including career success (Greenberg & Nilssen, 2015). It is thus important for researchers to examine and understand the link and effectiveness of existing STEM education models based on empirical evidence. This would not only indi- cate the immense scope that may lay ahead in terms of needed action by practitioners, but would also inform the design and implementation of joint action plans by stakeholder for enhancing STEM education outcomes for economic growth and development. This study may be useful as a catalyst for scholars to develop multidisciplinary theoretical models upon which propositions at the abstraction level can be advanced and empirically tested to progress knowledge in non-cognitive attributes, entrepreneurship skill, pedagogy and policy framework to support STEM education.
Conceptual and theoretical underpinnings Justification for STEM education
Quality education in general has a key role to play in enabling learners acquire compe- tences to function and adapt flexibly to rapid changes in a highly interconnected and hyper competitive world (Sanders, 2012). Proper education enables participants achieve knowl- edge, values, skills, beliefs and perspectives required to understand life (Voog & Roblin, 2012; Margot & Kettler, 2019; Li, 2014). This is the basis upon which countries invest in education and undertakes several initiatives to improve teaching and learning in schools.
But given the economic, social and environmental challenges, many countries and global institutions have taken STEM education in particular to constitute a dynamic and critical part of skill development process that is essential in inducing responsiveness to existing sustainable development challenges. Evidence based literature submits a view that STEM education is fundamental in facilitating sustained economic development and the attendant
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improvement in standards of living for the citizenry (Williams, 2011). A strong presence in STEM based occupations has been shown to be useful because many of the innovations that enhance productivity are from industries and occupations based on STEM education (Wan et al., 2016). As labour market demands shift to accommodate developments in tech- nology, consumer tastes and service preferences, employers are voicing their desires for innovators, problem solvers, team players, especially those with a strong STEM training background.
STEM education is therefore proposed as a response to depressed economies in that it can enable countries pursue industrialization and economic diversification for economic growth and development (Williams, 2011). Knowledge and skills development in STEM related occupations can also help in curbing unemployment, which arises because potential employees lack the skills to match changes in job specifications which arise from develop- ments in information and communication technology (Burnett & Jayaram, 2012). Twenty- first century jobs have been shown to require competencies in information literacy, techno- logical literacy and ICT literacy (Voogt & Roblin, 2012). Being information literate implies ability to access and critically evaluate information in an efficient and effective manner.
Being literate in ICT does not only refer technical skills, but also use of digital technology, communications tools or networks useful in functioning of a knowledge society. Techno- logical literacy means possession of abilities to assess, comprehend and apply technology in developing solutions to current and future challenges problems (DeCoito, 2016; Wu & Rau, 2019). Positive STEM education outcomes have also been linked to improved com- petitiveness in the global economy by keeping pace with high-technology sectors in other parts of the world (Wan et al., 2016; Williams, 2011). According to Li (2014), STEM edu- cation can also make a positive contribution to voluntary, informal and domestic work by enhancing knowledge of hygiene, health, and agriculture, which by implication have an impact on food security.
Due to the importance of STEM education and the need to enhance positive outcomes, some scholars in more developed parts of the world have proposed that the teaching of science, technology, engineering and mathematics should be integrated into one subject at the secondary school level as a response to vocational needs and economic aspirations (Hooker, 2017; Williams, 2011). This proposition has however been criticized by other scholars who argue that the same lacks clarity and seems to undermine technology training (Ostler, 2012). Williams (2011) also argued that STEM subjects vary in terms of epistemo- logical underpinning, and these differences should be maintained (DeCoito, 2016; Hooker, 2017; Voogt & Roblin, 2012).
Personality attributes
Cognitive attributes such as intelligence and academic abilities that are more to do with working memory capacity and inductive reasoning ability have for decades been acknowl- edged as predictors of positive outcomes in academic achievement and career performance (Stankov & Lee, 2014; Greenberg et al., 2003). More recent studies have investigated non- cognitive constructs and found a number of meaningful relationships with other impor- tant factors in life (Barrett, 2014). Non-cognitive which is an omnibus term for a range of personal qualities such as self-concept, self-efficacy, conscientiousness, resilience, neu- roticism, self-confidence and self-management have been shown to have a positive correla- tion with factors such as academic preparedness, education achievement, job performance, well-being and success in later life (Durlak et. al., 2011). There have been several studies of
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trait neuroticism, which is a unique dimensional measure of personality thought to capture emotional stability and a temperamental sensitivity to negative stimuli Powell and Zietsch (2011). Non-cognitive attributes have variously been categorized by different authors using other terminologies including personality (McDougall, 1932), psychosocial (Erikson et. al., 1959), soft skills (Heckman & Kautz, 2012), social-emotional learning skills (Elias et al., 1997) and character skills (Tough, 2013) and grit (Duckworth & Yeager, 2015).
This implies that there are numerous competing personality models (Digman & Inouye, 1986). Evidence from empirical studies have shown that non-cognitive abilities are useful in developing the ability to synthesize knowledge and skills and apply them creatively to develop innovative outcomes and career success (Sparkman et al., 2012; Stankov & Lee, 2014). Harnessing and improving non-cognitive abilities have therefore been argued to be useful in enhancing leaners ability to reason cogently about information, manage time, get along with others, and persistence in other endeavors (Carlson et al., 2014).
Several studies have therefore sought to identify non-cognitive constructs considered to have the greatest impact in academic achievement and success in life (Greenberg & Nils- sen, 2015; Heckman and  Kautz 2014). For instance, Benner (2004) study identified criti- cal thinking, problem solving skills, teamwork, collaboration, creativity and innovation as important attributes. This finding was collaborated by Kautz et. al. (2014) research that came up with almost an identical list of attributes. Other studies such as Costa and McCrae propose (1995) proposed six moderately varying dimensions of conscientiousness, that is, self-discipline, competence, dutifulness, order, achievement striving and deliberation, while Garcia (2014) identified persistence, teamwork, creativity and communication skills as important variables that impacted on the relationship between students and teacher.
Another perspective on non-cognitive attributes is by Farrington et al. (2012) who identi- fied academic perseverance, academic behaviors, academic mindsets, learning strategies and social skills. Other attributes include locus of control, self-esteem, emotional stability and self-efficacy (Judge & Bono, 2001); integrity, time management, self-control, leader- ship skills, creativity and teamwork (Kautz et al., 2014). Among the most common non- cognitive attributes referred to in numerous studies include Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience (Poropat, 2009). Many other related studies have suggested that non-cognitive attributes which had for a long time been taken to be a product of nature and nurture in early childhood, are actually pliable (Trap- mann et. al., 2007). Roberts et al. (2006) study for instance established that personal quali- ties such as agreeableness, conscientiousness, social vitality, social dominance, emotional stability and openness to experience keeps on varying throughout ones’ lifespan.
There is therefore a myriad of approaches that have been put forth as propositions for assessing non-cognitive characteristics in terms of their link to student achievement and career success, with an ongoing discourse on the pros and cons of each measurement tool (Carlson et al., 2014). Self-report as one of the most common approach to data collection has been critiqued for its susceptibility to socially desirable responding by study subjects who falsify or fake responses so as to present themselves in the most favorable light in order to fit in or be admired (Trapmann et. al., 2007). On the other hand, there is proposi- tion that other reports from teachers, guardian, counselor, parent, peer, coach, employer, subordinate, sibling, or numerous other people could be used (Poropat, 2009). The objec- tive being to gather relevant data from other sources who might have another perspective of the behaviors, personality, attitudes, beliefs and performance of the study object. But there is no consensus on which is the most suitable or effective assessment tool for non-cognitive attributes (Heckman & Kautz, 2012). Duckworth and Yeager (2015) however recommends
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adoption of a conglomerate of assessment and measurement methods in evaluating non- cognitive constructs.
Entrepreneurship skills training
The world is uncertain and having knowledge of an academic subject is no longer enough for a new graduate hence the need for entrepreneurship education which serves as a basis for creativity and innovation useful in succeeding in the 21st Century (Burnett & Jayaram, 2012). Skills taught in entrepreneurship such as financial literacy, collaboration, interper- sonal skills, money management and innovative mind-sets are important to STEM educa- tion graduates so as to enable them fully benefit from their innovations (Block & Stumpf, 1992; Mwasiaji, 2020; Sanders, 2012). Entrepreneurship skills training can enable STEM students develop ability to recognize commercial opportunities and skills to act on them (Austin, Stevenson & Wei–Skillern, 2006). Students who take entrepreneurship training are also taught how to develop self-confidence, opportunity recognition, concept com- mercialization, managing resources and initiating a business venture so as to create value for self and humanity by managing successful business ventures. Innovations from busi- nesses are critical for any society to be globally competitive, with technological advance- ments creating new jobs, new products, process or markets (Sinha et. al., 2011). Through entrepreneurship, communities improve their standard of living (Banjoko, 2012), ena- bles self-reliance by entrepreneurs after setting up businesses that allows them to reap the rewards for themselves (Haltiwanger et al., 2010).
If societies are to benefit from STEM education then students need to be equipped with training to do so. Entrepreneurship students are not only taught how to be creative and innovative, but also how to successfully start and effectively manage a business venture with the potential of providing a livelihood to the entrepreneur, close family and society (Henry et al., 2004; Mwasiaji, 2020). Through entrepreneurship training to facilitate cre- ativity and innovation, STEM graduates have an opportunity to reposition themselves in the business environment by redesigning their start-ups towards profitability for the longer term. Required entrepreneurship skills for starting and successfully managing a business venture include effective management of resources such as time, money and staff helps, all of which are useful in the achievement of set goals (Henry et al., 2004). Other entrepre- neurship related competencies include problem solving skills to enable planning and good decision making sometimes under pressure (Mwasiaji, 2020; Sinha et. al., 2011); Market- ing, sales and customer service skills to enable the entrepreneur to effectively promote his/ her products and provide good customer service (Henry et al., 2004); financial skills to enable forecast cash flow and sales, as well as monitor the profits and losses (Henry et al., 2004). Entrepreneurship skill training may therefore be useful in enabling STEM graduates bring their science and technology innovations into the marketplace, creates businesses with the potential to create employment and brings new products and / or services to the market place for the welfare of mankind. Through entrepreneurship skills training, STEM education graduates may be in a better position to mobilize funds, which can lead to capital formation, resulting in creation of wealth that is very essential for economic development (Haltiwanger et al., 2010). Such innovative businesses by STEM graduates especially those designed to take cognisance of the economic, social and environmental impact of their activities, would result not only in improving the society, but also help alleviate poverty and ensure that all people enjoy peace and prosperity (De Clercq & Voronov, 2011; Henry et al., 2004). Entrepreneurship training of STEM education students may present myriad
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opportunities to the society hence the need to investigate the interplay between non-cogni- tive attributes, pedagogical competencies and STEM education outcomes.
Pedagogical competencies
Teachers need to develop the knowledge and skills to enable them influence students’ behavioral change, respond to learner’s needs and create a safe learning environment in which students can learn and have fun (Sohoni, 2012). A good teacher is not only as good as the knowledge and skills he or she acquires and shares, but also the chosen instruction method. This observation may be connected to the rationale behind an emerging theme from research literature on the necessity for schools to successfully produce students capa- ble of talented contributions in STEM related occupations for economic, social and envi- ronmental benefits (Wan et al., 2016). This underlines the impact and importance of edu- cators and their competency in pedagogy which influences knowledge and skill transfer to learners in STEM education. According to Burnett and Jayaram (2012) and Williams (2011), pedagogy being the instructional approach implemented during the interaction between teachers and students in a class setting is important in determining STEM educa- tion outcomes. Having a well-thought-out pedagogy based on the content to be delivered and the entry behavior of learners can improve the quality of teaching by helping students gain a deeper understanding of fundamental material (Williams, 2011). Competency in pedagogy can enhance academic achievement, acquisition of technical skills, social and emotional development for learners, hence their ability to make a positive contribution to society (Burrus et. al., 2011a). Schools and stakeholders in the education sector must there- fore not only reorganize STEM curriculum to meet the changing needs, but also enhance instructional pedagogy in order to fully capitalize on students’ STEM potential (Gomez & Albrecht, 2013). The basis of this conclusion is empirical evidence on the role of a teacher and the chosen instruction method in impacting on students’ STEM identity and learning outcome (Johnson et al., 2015; Minichiello et al., 2018). Having a teacher who is compe- tent in pedagogy is particularly important because such a facilitator is best positioned to transfer knowledge to students as they also influence new and existing initiatives address- ing science identity and achievement in STEM education (Burnett & Jayaram, 2012; Wan et al., 2016).
Even though some studies are in agreement on the need for effective pedagogy, there is however no universal agreement on any of the range of approaches to be adopted so as to optimize positive learning outcomes (Nadelson et. al., 2013). One of the identified chal- lenges is in deciding which teaching methodology to adopt to deliver content in such a way as to meet the diverse needs of all learners with various cognitive abilities (McLeod, 2019; Elliott et. al., 2000). Another concern is that though teachers might be technically sound in their subject areas, there is still need to bring into line the teachers’ pedagogy and the curriculum pedagogy as intended by the content developer (Bagiati & Evangelou, 2015).
Numerous studies have therefore suggested that pedagogy needs a fundamental shift away from teacher-led instruction method to student centered-approach that allows learners to find their own way during the lesson (Lesseig et al., 2016; McLeod, 2019; Elliott et. al., 2000). The downside of the teacher centered method which relies on strategies such as whole-class lecture, notes memorization and chorus response to call approach, is that stu- dents tend to complete only lower-order tasks and might be afraid of the teacher (Nadelson et. al., 2013). On the other hand, student led approach also referred to as constructivist, participatory or active learning is said to be very effective, though it can also be difficult to

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