Tags: creativity, curriculum, curriculum design
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With an ever increasing focus upon the need to develop graduates with high level creative, risk-taking, and entrepreneurial skills, it is more important than ever to explore our approaches to the teaching-learning process. Graduate teachers need to be able to design, plan and deliver exciting, engaging and innovative learning opportunities. This article argues that the approach to planning, whether formal or informal, needs to be considered in relation to developing creative learning activities and creative learning environments. We need to start questioning the processes we use to plan the types of learning environments and activities that encourage the development of creativity. This article explores different approaches to planning and asks, ‘are we using the most effective approaches to planning to ensure creative skills are developed?’
Rationalistic, technical curriculum planning has been the dominant model underpinning planning for teaching and learning for a generation or more in England and Wales (Parkay and Hass, 2000) and involves the use of a linear approach to planning, which begins with the specification of objectives and ends with a lesson evaluation. This dominant or ‘rational’ approach to planning is based on Tyler’s (1949) model of curriculum theory and practice, comprising a systematic approach based upon the formulation of behavioural objectives. This approach provides a clear notion of outcome, so that content and method may be organised and the results evaluated. It considers education to be a technical exercise of organising the outcomes or products of learning, whereby objectives are set, a plan drawn up and applied and the outcomes (products) measured. Snape (2013) provides an example of what he defines as ‘quality learning’ through such a technical, sequenced linear pathway, including: the intended learning; teaching episodes; opportunities for tangibly evidenced student work; and criteria for successful achievement.
Several alternative and adapted planning approaches are present in the current literature, which are particularly pertinent to when requiring a more creative, risk-taking approach to teaching and learning, for example in Technology education. The ‘naturalistic’ or ‘organic’ model, based on the work of Stenhouse (1975) and Egan (1992; 1997), was developed from the apparent conflict between the need to carefully specify learning intentions and the dynamic nature of classrooms, and was an attempt to emulate a realistic planning process based on the ‘natural’ interactions in a classroom. Naturalistic planning involves starting with activities and the ideas that flow from them before assigning learning objectives (John, 2006). Although lacking detail in terms of pedagogical requirements and consideration, this model does resonate with Perkins, Tishman, Ritchart, Donis and Andrade’s (2000) notion of ‘learning in the wild’, when learning settings are recognized as ‘messy and complex’ (Carr, 2008: 36). Perkins and Saloman (1992) argue for the need for learners to experience more ‘natural’ learning environments, with teachers’ planning procedures supporting this notion.
Within a creative or problem-solving learning space – for example, in a Technology education context – ‘wicked problems or tasks’ (Rittel and Webber, 1973) can be set. These are described as ‘problems of deciding what is better when the situation is ambiguous at best’ (Marback, 2009: 399), and support the ‘naturalistic’ model, as wicked problems are not solvable. These problems are contingent problems of deciding what to do. They require continual evolution and, as such, are based upon the continual morphing of ideas and idea development, through a problem- solving process (Kimbell, Saxton and Miller, 2000). Such a ‘naturalistic’ model requires teachers to plan and create realistic design scenarios in order for students to learn the authentic nature of design activity, thus allowing students to experience environments where experimentation and exploration are dominant approaches.
The ‘interactional method’ of planning, another alternative to the dominant model, stresses the interactive nature of learning and, therefore, learning objectives (Brady, 1995; Bell and Lofoe,1998). Whilst the ‘interaction’ model specifies the same design elements as the linear objectives model, the ‘interactional method’ planning process can begin with any of the elements. Based on this model, all curriculum elements interact with each other throughout the design/planning process and, therefore, the design of one element will influence and possibly change the design decisions for other elements. For example, method might be specified first, but altered later as a result of an assessment decision. From a practical perspective, this model makes it possible to specify learning objectives after all other elements have been decided (Bell and Lefoe, 1998).
The ‘articulated curriculum’ (Hussey and Smith, 2003: 360) provides a similar approach to the ‘interactional model’, where the respective elements exist in a state of mutual interaction and influence. Alexander (2000) compares this ‘articulated curriculum’ approach to planning to the structure of a musical performance, where the composition is analogous to the lesson plan, and the performance shifts according to interpretation and improvisation. This ‘responsive’ approach to planning requires the teacher to be vigilant of the learning progression within the class and respond accordingly, and is synonymous with the formative assessment principles of ‘feedback’ (Ramaprasad, 1983). Biggs’s (1999) notion of constructive alignment also supports this way of approaching planning for teaching and learning.
To allow students to develop creative, risk-taking, critical thinking and problem-solving skills, we as educators need to provide authentic opportunities for students to develop such skills. By using different approaches to planning, teaching and learning, a greater range of ideas are produced and consequently new and innovative teaching and learning environments are potentially developed. Arguably by generating a creative input into the initial stages of the teaching-learning process, we are more likely to not only produce a creative output, but maintain creativity and innovation throughout the process. I believe it is important for pre-service teachers to have the opportunity to explore different approaches to planning, to develop their own approaches and styles, and to identify planning approaches that support the nature of the subject being taught.
Alexander, R. (2000). Culture and Pedagogy. Oxford, UK: Blackwell.
Bell, M., and Lofoe, G. (1998). Curriculum Design for Flexible Delivery- Massaging the Model. In R. Corderoy (ed), Flexibility: The Next Wave. Wollongong, Australia: Australian Society for Computers in Tertiary Education.
Biggs, J. (1999). Teaching for Quality Learning at University. Buckingham: SRHE and Open University Press.
Brady, L. (1995). Curriculum Development. Australia: Prentice Hall.
Carr, M. (2008). Can assessment unlock and open the doors to resourcefulness and agency? In S. Swaffield (ed.), Unlocking Assessment, 36-54, Abingdon, UK: Routledge.
Egan, K. (1992). Imagination in Teaching and Learning. Chicago: University of Chicago Press.
Egan, K. (1997). The Educated Mind: How Cognitive Tools Shape Our Understanding. Chicago: University of Chicago.
John, P. (2006). Lesson planning and the student teacher: re-thinking the dominant model. Journal of Curriculum Studies, 38 (4), 483-498.
Hussey, T., and Smith, P. (2003). The Uses of Learning Outcomes. Teaching in Higher Education, 8 (3), 357-368.
Kimbell, R., Saxton, J., and Miller, S. (2000). Distinctive Skills and Implicit Practices. In J. Eggleston (ed.), Teaching and Learning Design and Technology, 116-133. UK: Continuum.
Marback, R. (2009). Embracing Wicked Problems: The Turn to Design in Composition Studies. National Council of Teachers of English, 61 (2).
Parkay, F. W., and Hass, G. (2000). Curriculum Planning. (7th, Ed.) Needham Heights, MA, USA: Allyn and Bacon.
Perkins, D. N., and Salomon, G. (1992). Transfer of learning. International Encyclopedia of Education, Second Edition. Oxford, UK. Pergamon Press. [online]. Available at: http://www.cdtl.nus.edu.sg/Ideas/iot18.htm [Accessed on 31 March, 2013]
Perkins, D., Tishman, S., Ritchart, R., Donis, K., and Andrade, A. (2000). ‘Intelligence in the wild: a dispositional view of intellectual traits’. Educational Psychology Review, 12 (3), 269-93.
Ramaprasad, A. (1983). On the definition of feedback. Behavioural Science, 28, 4-13.
Rittel, H. J., and Webber, M. (1973). Dilemmas in General Theory of Planning. Policy Sciences, 4, 155-169.
Snape, P. (2013). Quality Learning for Technology Education: An Effective Approach to Target Achievement and Deeper Learning. PATT conference, 137-145. Canterbury: University of Canterbury.
Stenhouse, L. (1975). An Introduction to Curriculum Research and Development. London: Heinemann.
Tyler, R. (1949). “How Can Learning Experiences be Organised for Effective Instructon?” Basic Principles of Curriculum and Instruction. Chicago, USA: University of Chicago Press.
Dr Mary Southall is currently the Curriculum Advisor for the School of Education, having worked in the UK as an independent education consultant for over ten years. Prior to this, she worked as a design and technology teacher in a range of school contexts and was involved in the development of the National Strategies embedded in all secondary schools in England and Wales.
Tags: positive psychology, teacher education, teacher wellbeing
Teacher stress is high; in fact teachers exhibit higher levels of stress than any other profession (Stoeber & Rennert, 2008). Whether this be day to day stress related to required tasks, or stress due to institutional stress factors, teachers are struggling (Curry & O’Brien, 2012). As teachers battle exhaustion, so does their ability to cope and remain buoyant in the face of the increasing social and emotional demands placed on them, which directly impacts wellbeing (Parker, Martin, Colmar, & Liem, 2012). How do I know this? Because I too am a teacher.
Supporting teacher wellbeing is crucial because:
“Teachers worn down by their work exhibit reduced work goals, lower responsibility for work outcomes, lower idealism, heightened emotional detachment, work alienation, and self-interest. When teachers become burned out, or worn out, their students’ achievement outcomes are likely to suffer because they are more concerned with their personal survival.” (Richardson, Watt, & Devos, 2013, p. 231).
A study in the UK went one step further to show that teacher wellbeing had a direct impact on students’ SAT scores with a variance of 8%. This means teacher stress and wellbeing has a direct impact on student outcomes (Briner & Dewberry, 2007).
Wellbeing is a broad and complex area that, when discussed in a school arena, is typically centred on meeting student needs. Yet go into any staffroom and the topic of conversation will be centred around how tired, stressed and overwhelmed teachers feel. While burnout is high in experienced teachers, of greater concern is the attrition rate of beginning teachers who leave the profession because of a “lack of congruence between expectations for one’s career and the actual reality of the work” (Curry & O’Brien, 2012, p. 179). The one thing we do know is that in order for students to be well, teachers themselves must also be well (McCallum & Price, 2010). So, what are we doing to support teacher wellbeing? More specifically, what are we doing to better prepare pre-service teachers who are entering the profession?
Thankfully, we are now starting to see interventions that support teacher wellbeing beginning to feature alongside student wellbeing programs (Jones et al., 2013). A major contributor to this could be the rise of evidence based interventions coming from the field of Positive Psychology. Positive Psychology is a field of inquiry concerned with what makes communities and individuals thrive (Waters & White, 2015). Instead of exploring a deficit model of what is not working by asking questions such as ‘what is causing teacher stress?’, it looks at what is working by asking ‘what does teacher wellbeing look and sound like?’
This means sharing with existing and pre-service teachers about the numerous domains of wellbeing and their associated interventions. These may be in the form of Seligman’s 5 pillars known as PERMA (2011), the 6 domains of psychological wellbeing by Ryff and Keyes, (1995), or the ten items for flourishing by Huppert and So (2001) . By giving teachers evidence based tools to strengthen their wellbeing, we are not only building well teachers, we are preparing them for how to better teach wellbeing to young people with simple and practical strategies. These interventions can range from reflecting on being our best possible selves, keeping a gratitude journal, performing random acts of kindness, working with growth mindsets, setting and achieving goals, and identifying character strengths.
This does not mean we throw out the good work that is already being done in teacher education; it means we need to review what is working well and plan for ways we can more specifically address these positive interventions. Just as we explicitly teach wellbeing to young people, we must also explicitly plan ways to build a more sustainable workforce.
Briner, R., & Dewberry, C. (2007). Staff well-being is key to school success. London: Worklife Support Ltd/Hamilton House.
Curry, J. R. P., & O’Brien, E. R. P. (2012). Shifting to a Wellness Paradigm in Teacher Education: A Promising Practice for Fostering Teacher Stress Reduction, Burnout Resilience, and Promoting Retention. Ethical Human Psychology and Psychiatry, 14(3), 178-191.
Howard, S., & Johnson, B. (2004). Resilient teachers: resisting stress and burnout. Social Psychology of Education: An International Journal, 7(4), 399-420. doi: http://dx.doi.org/10.1007/s11218-004-0975-0
McCallum, F., & Price, D. (2010). Well teachers, well students. The Journal of Student Wellbeing, 4(1), 19-34.
Parker, P. D., & Martin, A. J. (2009). Coping and buoyancy in the workplace: Understanding their effects on teachers’ work-related well-being and engagement. Teaching and Teacher Education, 25(1), 68-75. doi: http://dx.doi.org/10.1016/j.tate.2008.06.009
Richardson, P. W., Watt, H. M., & Devos, C. (2013). Types of professional and emotional coping among beginning teachers. Emotion and school: Understanding how the hidden curriculum influences relationships, leadership, teaching, and learning, 229-253.
Seligman, M. E. (2012). Flourish: A visionary new understanding of happiness and well-being: Simon and Schuster.
Stoeber, J., & Rennert, D. (2008). Perfectionism in school teachers: Relations with stress appraisals, coping styles, and burnout. Anxiety, stress, and coping, 21(1), 37-53.
Tags: learning communities, learning theories, teacher beliefs, technology and education
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If we could equate teaching to learning, how would we account for the gaps in students’ achievements even though the students were taught by the same teacher and learnt in the same environment? If students could learn deeply by listening quietly to a teacher, would the traditional way of schooling be viable for our digital generation? Few people will deny the need to reconceptualise the notion of learning when digital media is shaping how learning is taking place in the classroom and beyond the confines of its walls. Learning sciences research is offering us lenses to understand the science of learning, knowledge construction, digital media, and principles of effective learning environments and the role of instruction.
What is Learning Sciences?
By learning sciences, we are not referring to how science is learnt. Rather, we are referring to an interdisciplinary field that investigates teaching and learning in various settings using theories and models from different fields such as cognitive science, educational psychology, instructional science, computer science and literacy studies. We are particularly interested in deep learning which is one of the scholarly inquiries in learning sciences. Like other learning scientists, we are interested in findings ways to understand and design innovative approaches to develop deep learning. By way of introducing learning sciences, we will present brief descriptions of some research areas in this field in the remaining parts of this blog.
What should Educators Know about Cognitive Architecture and Instructional Design?
A key research focus in the learning sciences is the design of learning environments that align with human cognitive architecture. Two key components of this architecture are working memory and long-term memory. Working memory can only process 2-4 elements of new information at one time (Cowan, 2001). Long term memory consists of schemas and has no known limitations.
Research on human cognition has generated a range of practical take-home messages for educators:
- In general, teachers should employ direct-guided instruction when introducing students to new learning materials. Guided instruction includes the heavy use of worked examples, particularly with well-structured problems, whereas unguided instruction requires students to adopt general problem-solving approaches such as trial and error and means-ends analyses which are heavily taxing on working memory.
- When students have developed a sufficient level of knowledge in a learning domain, teachers should not provide guided instruction. High knowledge learners have schemas in long term-memory to guide them when solving problems. However, when presented with external guidance by the teacher, these high knowledge learners are forced to mentally integrate the information provided by the teacher and cross-reference this with their own knowledge. This results in cognitive overload of working memory.
- Teachers should avoid situations which result in the redundancy effect. A common example is when a teacher uses a Powerpoint presentation and reads the text, word-for-word, from the slide. Such an approach causes cognitive overload because learners must attend to two streams of data which are conveying the same information.
- The spatial presentation of multiple sources of mutually-referring information can also lead to cognitive overload. For example, graphics and associated explanatory text are often placed separately from each other. Learners have to attend to both sources of information, because in isolation, neither source conveys the full information needed for the learner to problem solve. The cognitive resources required by learners to mentally integrate the separate sources of information are highly taxing on working memory. The solution is to physically integrate the two sources, thus reducing the search and match processes required by learners to understand the information presented.
Are Positive Learning Environments All about Developing ‘Feel Good’ Schools?
In our inquiry about the design of learning environments, we are also keen to examine the association between school environments and student’s wellbeing. Debates in this focus may conjure up outdated notions of teachers minimising scolding of students to preserve their self-esteem or schools saturated with posters reminding students that they are unique. There are educators who are incredulous of new curricula which invite both students and staff in schools to look at their emotional development. They most probably see it as far removed from the core business of schools and only contributing to ‘feel good schools’ which have little impact on important things in life.
Positive Learning Environments (PLE) are places of learning where the whole of person is engaged in an effort to contribute to the overall development of an individual and in turn his or her communities. The ‘positive’ is both an indication of the more traditional sense of pleasantness and safe, but also a mathematical concept of ‘addition’. It involves adding, contributing to an individual’s development. In PLE, knowledge of the factual traditional curricula of schools is intertwined with knowledge and development of the whole of self. This invariably includes an incorporation of affect in the everyday practice of schools. Affect, in this instance refers to not just the experience of feeling or emotion but also the physiological and cognitive (thinking) components of such experience. Although affect and knowledge acquisition have always been part of learning anything by anyone, it is fair to say that systematically talking about, intervening in and considering affect regulation, quality and development as part of schooling is a relatively new phenomena for schools to take on.
The detrimental impact of aversive affective states (e.g., anxiety) and school environments with components related to high affective dysregulation for students and staff (such as racism, bullying and violence) on learning and wellbeing are now well documented. However, the need for research and development of positive learning environments is not just about the removal of unpleasantness in schools. It is also about the gains which are made when affect regulation and development are also seen as the core business of schools alongside academic development. This research is exemplified by current efforts looking at social and emotional learning (SEL) in schools. SEL is defined as a process engaged in schools where all members of their communities apply themselves to the development and understanding of emotions with an understanding that “learning emerges in the context of supportive relationships that make learning challenging, engaging and meaningful” (CASEL, n.d.).
The economic and lifetime benefits of social emotional skills and schools’ unique position to develop them have also been acknowledged in a recent OECD report (see OECD, 2015). The report highlights and acknowledges the increases in access to education but recognises that social emotional skills are needed alongside academic/cognitive skills to foster lifetime success. It is through affect regulation (directly or as a mediator of other skills) that greater cooperation, task perseverance, and problem solving can be achieved by communities and individuals. Although current available evidence in relation to social emotional learning is growing and promising, there is still much to be discovered. What are the key skills our teachers need to engage in SEL? Are the effects of SEL universal? How do we best develop social emotional skills? For that matter, which skills do we develop? What are the best pedagogies that engage the whole of the child and how do we assist our school system to evolve from a system whose origins gave little credence to emotion to ones where knowledge and affect are treated as one.
Positive learning environments are more than just ‘feel good’ schools. They are active learning communities engaged in the education of the whole child for their and their communities benefit. They are complex communities with relationships, processes, and pedagogies directed at affect regulation and cognitive development practices. They are truly the 21st century schools.
Why Should We Study Teacher Beliefs?
In our inquiries into designing learning environments, we are not forgetting the importance of understanding teacher development and beliefs. Teachers develop a sophisticated amalgam of knowledge, beliefs, and skills to be effective in the classroom. In particular, teachers’ beliefs about teaching and learning can provide useful insights into their practice. Beliefs are “psychologically held understandings, premises, or propositions about the world that are felt to be true” (Richardson, 1996, p. 103). Teachers’ beliefs can be classified into views of the teacher’s role in the classroom, the students’ role in the classroom, how the students learn their subject area best, and how to make the subject matter comprehensible to others (Friedrichsen, van Driel, & Abell, 2011). These types of beliefs are often derived from prior K-12 school experiences. They are extremely robust and do not change easily (Jones & Carter, 2007).
Often, teachers are asked to implement new pedagogies in their classrooms that align with current reform efforts (e.g. inquiry-based approaches). Yet, teachers often experience considerable difficulty when implementing new pedagogies as they develop practical knowledge and perceptions of their school contexts. Practical knowledge and perceptions of context are then filtered through core beliefs about teaching and learning which can impact classroom practice. For example, consider a teacher who has just implemented an inquiry-based approach to instruction. After implementation, constraints may develop in the form of practical knowledge suggesting that students have considerable difficulty with the task. The teacher may also develop perceptions of his or her school being unsupportive of reform-based strategies. If the teacher also believes his or her role is to only transmit information to the students, this will likely cause him or her to abandon the strategies. Conversely, in the face of practical and contextual constraints, if the teacher believes it is his or her role to facilitate guided inquiry experiences so that students have some opportunity to wrestle with the concepts, he or she is likely to make modifications to his or her teaching and attempt the pedagogical strategies again (Sickel & Friedrichsen, 2015).
With the example above, we see that helping teachers elucidate and often confront their existing beliefs about teaching and learning is an important part of the teacher development process. A teacher with core beliefs that misalign with a teaching approach is a significant barrier to large-scale implementation. Understanding teacher learning provides important implications for designing teacher education and professional development programs which in turn help teachers enhance their students’ learning outcomes.
How has Digital Media Revolutionised the Way Students Learn?
Increasingly, learning sciences calls for an inquiry into students’ perspectives and the ways in which their literacies are accessed, used and lived in everyday practices, both inside and outside of school (Kim, Tan, & Bielaczyc, 2015). Existing learning sciences research shows an increasing interest in the emerging culture of learning in the virtual spaces. We sum up how students are self-directing themselves online using 5Cs of what they do in this emerging culture of participating online:
- Students are staying connected to their peers and interest-based groups to pursue passion-based learning.
- Often, these students are learning about a specific content or skill from mentors who may not necessarily be adults but have enough experience to share their knowledge with them.
- Students are displaying more ownership of their creative works or digital artefacts Using social media, they communicate their thoughts and “pass on” their works to solicit feedback and appreciation.
- They create networks to stay connected and communicate with people who share their interests and are keen on what they do.
- Learning becomes more distributive and social. Nonetheless, with the diverse backgrounds of people whom they interact with online, learning has evolved from simply group learning to collaborative learning where multiple perspectives of a focused issue are exchanged before a shared perspective is established.
- Conversations no doubt can include playful talks but have become more dialogic to facilitate deeper thinking in online interactions.
- Digital artefacts provide strong evidence of learning. When students interact with others online, learning has become more participatory. To learn from one another means there must be learning by doing.
- There are more bodies of research that show students are developing dispositions of experts as they learn by doing and intentionally cultivating thinking skills which classroom teachers are trying to develop in key content areas in the formal learning spaces.
- With learning becoming more distributive, collaborative and participatory, students are developing ways of managing their works and feedback online. Curation becomes part and parcel of what they do such as creating tags to organize their online artefacts.
- Students are looking for ways to exhibit and curate their current and past works using social media using Google Plus, Facebook or using apps to create their own websites.
In order to pursue our work in learning sciences, we have formed the LƩARN (Learning Sciences Affect Research Network) HDR cohort group. This is a group uniquely created for HDR students within the School of Education to embark on research related to the field of learning sciences. To build our student’s research capacity, we are conducting a series of workshops and forums in the second half of 2016. You are welcome to contact anyone of us for further information about this group and the research we do. We also welcome any comment and feedback from you regarding our research interests or activities in LEARN.
Researchers in LΣARN
|Dr Lee Chwee Beng
|Dr Aaron Sickel
|Dr Lynde Tan
|Dr Jose Hanham|
|Dr Roberto Parada
CASEL. (n.d.). Collaborative for academic, social and emotional learning. Retrieved from http://www.casel.org/social-and-emotional-learning/
Cowan, N. (2001). The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87–114.
Friedrichsen, P., van Driel, J. H., & Abell, S. K. (2011). Taking a closer look at science teaching orientations. Science Education, 95(2), 358-376.
Kim, B., Tan, L. & Bielaczyc, K. (2015), Learner-generated designs in participatory culture: what they are and how they are shaping learning. Interactive Learning Environments, 23(5), 545 – 555.
OECD. (2015). Skills for Social Progress: The power of social and emotional skills. Retrieved from http://www.oecd-ilibrary.org/docserver/download/9615011e.pdf?expires=1461906844&id=id&accname=guest&checksum=B24ED59A273470F52724E55D6AA51152
Richardson, V. (1996). The role of attitudes and beliefs in learning to teach. In J. Sikula (Ed.), Handbook of Research on Teacher Education (pp. 102-119). New York, NY: Simon & Schuster Macmillan.
Sickel, A. J., & Friedrichsen, P. J. (2015). Beliefs, practical knowledge, and context: A longitudinal study of a beginning biology teacher’s 5E unit. School Science and Mathematics, 115(2), 75-87.