Positivity and the Learning Environment; Facilitatory factors in ‘successful’ Secondary Education

1. Introduction

The educationalist John Dewey (1916) proposed a philosophy of education emphasising experimentation, habitual reflection and interactions between educator and pupil. Joint teacher-student observations were crucial in assessing educational cause and effect (i.e., how observing given conditions, ordering their use, and considering alternatives might change educational outcomes) which in turn improved foresight, until the process became student-led.  Learning in this way enabled capacity for growth, whereas externally-set mechanical activities were considered limiting. In contrast, most current support structures for UK secondary school-aged students arguably view learning as a primarily cognitive endeavour, with less emphasis placed on relationships between actors in the learning environment. Often, by design or practicality, they preclude the learner reflection Dewey holds paramount.

Here, 11–19-year-olds in UK secondary education will be the focus. This decision springs from several considerations highlighting the importance of this scholastic period. For example, Ofsted (2015, p1) reports that for many, the first three years of secondary education are ‘wasted’, whilst the Social Mobility Commission (2017) suggests the poorest students may see primary school progress practically eliminated. This leads us to question the source of such different experiences and potential resolution of their negative impact. Thus, this project will explore what authentic learning is, what factors facilitate the process of authentic learning, the effect of learning environment, and why some individuals are more ‘successful’ and/or engage more intuitively with facilitatory factors than others.

1.1 What is learning?

Before considering factors affecting learning, it is important to consider its broader context; definitions vary greatly by discipline (education, psychology, biology etc.). Although finding consensus is extremely difficult (Wiliam, 2017), three commonalities emerge. Firstly, learning begins with active acquisition of new knowledge, behaviour and/or capability (e.g., Knowles et al., 2011; Hattie, 2009, 2012), building on prior knowledge, behaviours and/or capabilites (e.g., Clark & Mayer, 2011). Secondly, newly acquired material/skill should be retained over time, with a degree of permanence (e.g., Kimble, 1961; Kirschner et al., 2006; Soderstrom & Bjork, 2015; Didau & Rose, 2016). Thirdly, acquisitions should be successfully applied when later required (e.g., Black & Wiliam, 2009; Alexander et al., 2009). An important part of this project will be to establish what learners, educators, and those outside education perceive ‘learning’ to be. However, at this point the three aspects above will form a working definition.  

1.2 What is being learned: Knowledge objects and modularity

Radical Empiricism reasons that everything real must be experienceable, and every kind of thing experienced must somewhere be real (James, 1912). Thus, ‘what’ is being learned may be more complex than it first appears. Moreover, Dewey (1916) suggested that active experiences cause shifts in understanding, from which ‘learnings’ occur (see also Kuhn’s paradigm shifts; 1962, p85). Peirce (1878) considered ‘what’ had been learned as conceptually conceived “objects” with practical applications; the process of forging the object itself affects the “whole object” conceived (i.e., process affects outcome). Popper’s Three Worlds Theory (1972) splits perceived reality into internally constructed domains of 1) physical things and events, 2) mental processes, and 3) logic derived from thought. Each world contains “knowledge objects” and learning is the outcome of gaining them, regardless of their form. As Knowledge Objects also describe the knowledge, behaviours and capabilities seen in definitions of learning, this term will be used below.  

That said, it is clear that opinions on how the brain processes knowledge objects can differ. For example, Foder (1983) views the ‘mind’ as modular, with information processing in a module unaffected by information in the rest of the brain. In contrast, Hattie (2009) sees the process of constructing knowledge as a philosophy of ‘knowing’, not ‘learning’ per se, but emphasizes its importance to learning overall. However, the brain’s processing of informational input – and its key role in successful knowledge acquisition/retention - is consistent across accounts, although how educators can best support this process (philosophically and mechanistically) is the subject of continued debate (e.g., Hattie, 2009; Rosenshine, 2012; Kirschner et al., 2006; Willingham, 2009; Dunlsoky et al., 2013; Hendrick & Macpherson, 2017).

1.3 Constructivism and cognition

Broadly speaking, cognitive processing can be seen to control bodily activity creating behaviour; Cognitive psychology examines mental processes underlying this (e.g., learning, perception, memory, language, reasoning and problem-solving; Neisser, 2014). Constructivism sees learning as a cognitive process, with new information added to an individual’s current structure of knowledge, understanding and skills. Here, learners are in partial control of acquisition, which is most efficient when individuals are active in its construction (Pritchard, 2018).  This control is dependent on motivation, attitude, age, intelligence, aptitude, cognitive style, and personality (Ellis, 1985), although external factors such as learning environment, instructional design, peer and teacher relationships and home situation may also contribute.

Paiget (1963) proposed that young learners construct knowledge and understanding, by acting as lone scientists undertaking logical trials and subsequent improvement; such processes change with age, creating a stage theory. Two of these stages are important to this project. Firstly, the Concrete Operational Stage (from 7-12 years) indicates when children’s logical thought develops and this understanding shows a degree of permanence (cf. simple object recognition). Secondly, the Formal Operational Stage (adolescence to adulthood), denotes when knowledge contained within schemas (i.e., organizational/interpretative frameworks used during information acquisition and storage) can be used for inductive and deductive reasoning.  This acquisition and use of knowledge can be considered ‘learning’ if viewed statistically (i.e., an optimised reaction to a stimulus). For example, Barrett (2017) states that from birth, humans perform statistical predictions about what should happen in a given situation, and how they should respond to a given stimuli – over time statistical distributions change and individuals may respond differently to the same stimulus.

In contrast to Constructivism, Behaviourism (e.g., Watson, 1930; Skinner, 1957, 1961), suggests formal teaching in schools should be concerned with desired responses only, with behavioural reinforcement increasing the likelihood of these desired responses. Via Skinner’s Operant Conditioning, punishment and reward are seen as the key drivers in making non-desired responses ‘extinct’, consistent with the ‘policing’ role of the teacher (i.e., strict praise and discipline systems allow positive/negative reinforcement which force desired behaviours; Skinner, 1961).  Whilst uncommon, some educational models still include explicit Behaviourist principles (e.g., Birbalsingh, 2016), with the potential to impact wider expectation of secondary school educators and their default stance.

1.4 Memory and meaningful practice

After acquisition and processing, information must be remembered to evidence learning (e.g., Kimble, 1961; Kirschner et al., 2006). Ebbinghaus’ (1885) seminal work presented three mechanisms that support memorisation; 1) voluntary conscious recall, 2) involuntary conscious recall, 3) non-conscious recall. Collectively, these demonstrate that successful memorisation of information occurs when it is repeatedly presented over time. Many factors can impact the efficacy of this process (e.g., learning fatigue, time-of-day learning occurs, quantity of knowledge to be remembered, temporal distribution of practice; Zabrucky & Bays, 2012). However, even across this broad literature, most studies affirm Ebbinghaus’s basic premises for optimising retrieval of knowledge objects (Berntsen, 2007).

However, ‘in the moment’ performance is held as a poor indicator of long-term memorisation and learning (Soderstrom & Bjork, 2015), which questions how permanent memories must be before we consider them substantive learning.  Olsen & Ramirez (2020) suggest that habitual behaviour (cf simple stimulus-response linking) indicates learning, whilst Ericsson (1993) suggests the proficiency needed to demonstrate expertise requires 10000 hours of deliberate practice. By these measures, nothing is ‘learned’ quickly. Atkinson & Shiffrin‘s (1968) Modal Model of memory arguably provides a rationale for this in terms of the temporal factors in the process.  This model involves three separate components; firstly, the Sensory Register (SR) enables sensory information entry into memory. The Short-Term Store (STS) holds SR input, with limited capacity.  Finally, the Long-Term Store (LTS), with unlimited capacity, provides the ability for rehearsed information to be held indefinitely.

1.5 The rise and rise of Cognitive Load Theory

Atkinson & Shiffrin’s model highlights neural limitations affecting learning – notably limited capacity of the STS. Cognitive Load Theory (CLT; Sweller, 1988) builds on their model, indicating the primary factor in distinguishing experts from novices is retention of usable domain-specific knowledge (i.e., schemas). However, such complex cognitive processing is generally held to be problematic for learning, since it prevents effective schema acquisition (Sweller, 1998). CLT explores impact of cognitive inefficiency via ‘learning-loads’ (see also Atkinson & Shiffrin’s Modal Memory Model).  Here, intrinsic loads originate from conceptual difficulties in new information, which cannot easily be reduced. Germane loads depend on individuals, occurring with construction or update of schemas. Extraneous loads occur if instructional design is suboptimal – these can be reduced by consideration of task orientation and instructional design. Both can help reduce ‘load’ and control encoding processes, influencing how effectively a knowledge object is stored in memory (Craik & Lockhart, 1973).  

Studies in recent years (e.g., Rosenshine, 2012; Dunlosky et al., 2013) have suggested numerous supporting practices (e.g.  recall starters, explicit modelling, scaffolded solutions, spaced repetition, interleaving). Many such mechanisms are embedded within secondary education practice, receiving mainstream popularisation (e.g., Hattie, 2009 & 2012; Willingham, 2009; Didau & Rose, 2016; Weinstein et al., 2019). Prima facie, this provides an encouraging picture of the educational domain, however, recalling that secondary school years may be considered ‘wasted’ (Ofsted, 2015), why are such research-led practices not achieving the success they should be?  

1.6 Experimental and social learning

Theories of cognitive-centric learning are not alone in shaping secondary school practice. Sporadic popularity has emerged for reflective, experimental and social learning processes stemming from Dewey’s (1933) five phases of reflective thinking. These begin with learners mentally suggesting possible solutions to problems, which then develop into intellectualisation of the difficulty/ problem causes. Consideration of multiple solutions leads to hypotheses generation, which may elicit elaboration and imaginative action. Formalising these ideas, Vygotsky (1978) identified socially constructed learning within a Zone of Proximal Development (ZPD), comprising active learners, social interactions, and appropriately scaffolded challenge.  This construct can be applied directly to the learning environment.

For example, Bruner (2009, p33) suggests a pertinently designed ‘spiral curriculum’ can use experimentation to enable cognitive growth in ‘any child at any stage of development’. This learning is most successful when it becomes habitual (Bruner, 1996); thus, teaching becomes the vehicle by which the learner is encouraged to repeat experimentation and scaffolded practice. Similarly, Kolb and Fry (1975) describe learning as a cyclical process, ‘joinable’ at any point and containing concrete experience, reflective observation, abstract conceptualisation and active experimentation. To be successful, learners are required to be active and aware of the transformative experiences involved in knowledge creation (Kolb, 2014). These models place social interaction, experimentation and reflection at the heart of learning, but also indicate learners are key stakeholders in the process.

2. Where next?

2.1 Student centred learning & mastery

Many educators would hope to see an underlying ‘thirst’ for new knowledge/learning in their students. Using individual differences psychology, Maslow (1987) suggests human needs are hierarchical, from basic, to psychological and finally, self-actualization. While completion of each need stratum does not preclude progression, self-actualization can only be satisfied with active striving to reach full potential (and more basic needs adequately met). In this model, desire to ‘acquire knowledge’ and/or ‘understand’ are considered ‘cognitive’ self-fulfilment needs, while ‘learning’ can only be partly satisfied by free enquiry and a desire for facts.

McCourt (2019) identified Aristotelian ideals which consider educational knowledge acquisition as best supported by intricate one-to-one (1:1) tutoring; here, the tutor is aware of a student’s level of knowledge, how to build on it and/or correct erroneous thinking. Dewey schools in early 19^th century America (Dewey, 1916), and subsequent models (e.g., Winneka Plan; Washburne & Stearns, 1928), created an education system which saw teacher-student interaction as core.  Similarly, Mastery Teaching (Bloom, 1968) suggested best practice was replication of 1:1 tutoring scaled to a group. Indeed research (Bloom, 1984) showed 2 SDs performance improvement in in 1:1 tutored students (i.e., compared to conventional methods) and >98% better performance than a control group. However, if students are attentive and appropriate clear instruction is provided, Bloom (1968) suggested these mastery benefits could generalize to > 90% of students.

2.2 Social cognitive learning

From a socio-cognitive perspective, the construct of (Self) Agency (SA; Bandura, 2009) outlines an individual’s capability to exert influence over their own actions, and ability to adapt according to their goals. This generalises to Bandura’s (2006) Self-Agentic Theory (SAT), which firstly identifies individuals’ intentionality and forethought, aligned with both clear rationale and forward planning.  Further, Self-reactivity pairs with self-reflectivity, to enable checking and evaluation of outcomes.   High levels of SA increase an individual’s self-efficacy (Bandura, 1977, 1982); their perception of how well their actions address intended outcomes/goals (here, when learning). These outcomes can increase the likelihood of attaining self-set learning goals (Shunk & Green, 2017), which Bandura (1986) termed Social Cognitive Learning.

Another theory of Self-regulated (SR) Learning arose from these principles, comprising theoretical, conceptual, and practical elements (Zimmerman & Schunk, 1989; Schunk & Zimmerman, 1994; Zimmerman, 1998).  Here, extrapolating sub-functional SR (e.g., impulse control, goal-attainment processes) can support cognitive learning mechanisms, arising when learners selectively use metacognitive, motivational and behavioural strategies. Additionally, successful learners proactively select, structure and create advantageous learning environments, helping to choose the form/amount of instruction they need (Zimmerman & Schunk, 1989).  With arguably superior motivation and adaptive learning methods, SR students are not only more likely to succeed academically, but to view their futures more optimistically (Zimmerman, 2002).  Clearly, this idea might affect attainment in a straightforward manner, but it could also impact on holistic perception of education value, and progress in challenging domains.  Thus, evaluation, promotion and reinforcement of SR principles will be an important aim for this project

2.3 Attention, motivation, and goals

According to James (in Prinz, 2020, p2) “everyone knows what attention is – it is the taking possession, by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought”. This resonates with SA and SR learning in that we need to understand how learners decide which of various possible goals/outcomes to attend to, albeit at times in a metacognitive sense.  McCrea (2020) argues that for students, attention and motivation are correlated – what learners attend to is what they are motivated by and vice versa; thus, ‘Motivation’ is considered as a system for allocating attention towards or away from things taught.

 In more general terms, motivation has been described as a psychological phenomenon incorporating beliefs, expectations, goals, and intrinsic/extrinsic rewards; these may be dependent on social norms and whether learners are grouped (Didau & Rose, 2016). Ryan and Deci (2000) suggest motivations are often conflated as a single category, whereas three have been identified.  Heteronomous motivations are externally regulated rewards/ punishments that control behaviour, in contrast with introjections (internally regulated self-guilt/ criticisms). Finally, identifications are motivations due to belief in that being appropriate/consistent with norms; all produce different behaviours in terms of outcome and longevity. More specifically here, understanding motivation will illuminate how learners moderate behaviours, when deciding what future goal they will attend to.

More recently, Ryan & Deci (2017) observed a current unhealthy obsession with ‘distant’ outcome (i.e., with an extended time period and/or involving multiple steps). For example, if a student’s desired outcome is Grade 9 in English GSCE, distance and lack of specificity mean it may be too remote to be successful. Such goals tend to be policed by rewards and sanctions; processes which may be inherently detrimental to ‘successful’ learning. By contrast, effective goal-orientation can support student motivation and attention, provided students are aware of the differences in long term ‘distal goals’, and ‘proximal goals’, which are quickly achievable (Latham & Locke, 1991). Pintrich (2000) advocates teachers active support of student goal-setting, enabling creation of multiple goals with multiple pathways in multiple contexts. Similarly, Bandura (2006) suggests goal-setting is best supported by guiding mastery development, helping learners accept that success is hard-won, and showing failure as opportunity for improvement.

3. Why do we educate? Education as a moral and social endeavour.

Taken together, the aspects of the learning (and educational) processes outlined above illustrate the complexity of this project.  Should educators focus on the simplistic mechanisms held to underpin educational achievement (e.g., long-term memorisation of information)?  Or is there a broader requirement (and potentially, moral responsibility) to foster positivity in learners? This dilemma receives important attention within the pedagogical literature. Friere (1968) advocates for close relationships between student, educator, and society. He also suggests traditional pedagogy as a ‘banking model’ in which teachers are the owners and depositors of knowledge, although here, students are passive recipients only (Torres, 2019). Consequentially, students become non-critical thinkers, skilled in remembering facts, but unskilled in real world application/critical evaluation. In contrast (e.g., Freire, 1992), he goes on to describe fostering hope in students as ontological; he also stipulates relationships between students and teachers should be re-considered, as ‘education is suffering from narrative sickness wherein teachers narrate, and students listen’ (1993, p52). It is not difficult to argue that this is unlikely to promote happy, fulfilled educators or successful, contented students.

Overall, this literature suggests cognitive and constructivist approaches to secondary education are necessary, but not sufficient to foster successful long-term learning. To echo a point presented above, Wiliam (2011, p.14) states “a bad curriculum well taught is invariably a better experience for students than a good curriculum badly taught: pedagogy trumps curriculum. Or more precisely, pedagogy is curriculum, because what matters is how things are taught, rather than what is taught”. This sentiment gives exceptional clarity to the aims of this doctoral project. In summary, it will investigate how classroom educators might work with students to deliver this pedagogical approach. This will entail synthesis of current thinking/practice (e.g., insights gained from cognitive research), with the potential benefits of increasing learner positivity (e.g., self-efficacy, goal setting, self-regulation and reflection).

4. Progress Report

Progress since January 2020 has included substantial literature review, collaborative writing, research / data analysis training, and data collection, amidst the unique setting of the Covid 19 pandemic. For most of this time, part time study has been wholly unpredictable (i.e., with shifting staff/student school attendance patterns) and data collection plans unsustainable (for the same reasons). Although this has been frustrating, it has brought unexpected benefits (e.g., time for analytical skills training, use of research-relevant platforms/software).

My initial PhD proposal highlighted a number of avenues which could be explored in greater detail to provide a clear research focus. Fourteen years in secondary education have highlighted the outcomes of education-based cognitive research (e.g., retrieval practice; Craik & Lockhart, 1972; CLT; Sweller, 1988; desirable difficulties; Bjork & Bjork, 1992), and guided instruction; Kirschner et al., 2006).  However, my review activities have revealed fewer studies contextualizing secondary school learning, beyond straightforward cognition and/or prevalent theories of social learning. For example, applying the BBH (Fredrickson, 2001) to learners, or SA Theory (including aspects of intentionality and reflective practice; Bandura, 2006) to both learners and instructors may give more insight into the internalized contextual factors important to ‘success’. In addition, GS theory (Latham and Locke, 1991) indicating individual purpose (as regulated by an individual’s goals) may be seen as integral to learners’ academic performance progress. These phenomena (inter alia) are seen as important in education but are often not explicitly supported in schools. 

When considering these theories collectively, GS behaviour emerges as a focus for next year’s work. This mechanism will be useful to evaluate in learners of different ages, alongside a number of Individual Differences (e.g., measures of character strengths, mood/affect, self-efficacy and Big Five personality traits). Limitations of this preceding year have constrained the ability to run studies as initially planned; these are anticipated to run in 2021/22. The table below outlines studies which have been undertaken or are currently ongoing.