my thesis proposal

Facilitating Inquiry-Based Learning as a Complex Adaptive System

MA Education Administration Thesis Proposal
Sean Park 990957648

Supervisor: John Portelli
Second Reader: Malcolm Richmon


TABLE OF CONTENTS
1. TITLE 3
2. ABSTRACT 3
3. CONTEXT 3
4. INTRODUCTION/OVERVIEW 4
5. SIGNIFICANCE 5
.1. INQUIRY-BASED LEARNING 5
.2. COMPLEXITY LITERATURE 6
.3. EDUCATION ADMINISTRATION 7
6. LITERATURE REVIEW 7
7. THEORETICAL FRAMEWORK 8
8. CONCEPTUAL FRAMEWORK 10
.1. RESILIENCE AND COMPLEX ADAPTIVE SYSTEMS 10
.2. INQUIRY-BASED LEARNING 12
.3. THE PROPOSITIONS 14
.4. STORIES 20
9. METHODOLOGY 21
.1. JUSTIFICATION AND DESCRIPTION OF METHODOLOGY 21
.2. DATA COLLECTION 22
.1. FACILITATOR NARRATIVE DEVELOPED FROM REFLECTIVE JOURNALS 22
.2. RESPONSES FROM FORMER STUDENTS 22
.3. RESPONSES FROM SIX SCHOLAR-EDUCATORS 23
.3. ANALYSIS 23
.4. PARTICIPANTS 24
.5. RECRUITMENT 25
.6. RISKS AND BENEFITS 25
.7. PRIVACY AND CONFIDENTIALITY 26
.8. COMPENSATION 26
.9. CONFLICTS OF INTEREST 26
10. ANALYSIS 26
11. TIMELINE 28
1. Title

Facilitating Inquiry-Based Learning as a Complex Adaptive System

2. Abstract

This action research study examines the application of a set of guiding principles by a facilitator in an inquiry-based learning (IBL) environment. These principles are advanced as propositions for working with complexity in an undergraduate IBL environment. Complex phenomena are characterized by properties such self-organization, emergence, and nonlinearity and the educational implications of complexity has received little attention in the IBL, scholarship of teaching and learning, and educational administration literature. The experience of a facilitator running a small (18 students) undergraduate course on Complex Adaptive Systems (CAS) serves as the context for interpreting the propositions. A narrative constructed from the facilitator’s experience, along with responses from former students in the course, will be evaluated by six scholar-educators with backgrounds in either complexity and/or IBL. These evaluations will undergo analysis to create a revised set and a discussion on the direction and implications of this work will follow.

3. Context

This study aims to capture my journey into conceptualizing and facilitating an inquiry-based learning (IBL) undergraduate course as a complex adaptive system (CAS). My primary goal is to use the study as a context for understanding how educators with complexivist sensibilities might approach facilitation in an IBL environment. Before I describe the study I want to orient you to my broader aim of educating for resilience. It is my assumption that if students learn to be resilient through the complexity of their lives, they will be better at sensing out and adapting to change. A university instructor made the following list of things he sees students dealing with on a daily basis:

…roommates, friends, jobs, pregnancies, self-discipline needs, sickness, betrayal, fatigue, alarm clocks, parents, grandparents, cars, self-confidence issues, court appearances, sleep, self-esteem issues, boyfriends, time-management, confusion, divorce, discouragement, depression, children, girlfriends, partying, sex, alcohol, sexual preference, Facebook, working out, concerts, holidays, weddings, pets, sorority, fraternity, computer crashes, finances, food, grades, gender issues, drugs, accidents, disease, death, tests, papers, parking, femininity, boredom, masculinity, excitement, homesickness, weather, aloneness, loneliness, crushes, love lost, love gained, distance relationships, being "single," physical abuse, verbal abuse, tanning, prejudice, getting together, nails, breaking up, studying, weight, professors, coaches, GPAs, athletics, majors, hair, career futures… (Schmier, 2006)

These issues comprise the ‘complexity’ of being a student and it is my vision that education should facilitate the development of resilience within this complexity. Of course, who would want un-resilient people? Substantiating my vision requires that I address questions of What do I mean by resilience? and Why resilience and not something else? I will get to these questions in the thesis.

I also need to unpack the concept of facilitation. I use the word to mean that educators can only provide the conditions for learning and growth. Education and educators cannot ‘program’ people to be resilient, it is individuals, groups and communities alone that have the responsibility and capacity to become resilient. Facilitators are kind of like farmers, unable to grow crops but capable of setting some of the conditions. The rest must be left to ‘nature’.

My conceptions of facilitation, resilience, and complexity have everything to do with the nature of living systems. I believe that when we look at the processes that help all living systems to be resilient, we can understand how uncertainty, paradox, co-evolution, emergence and self-organization are at work in every educational encounter. Within and beyond each person exists a dynamic web of co-evolving relationships. These relationships involve interactions with physical environments, ideas, feelings and people.

Educating for resilience is about enabling people to consciously work with these relationships as part of an ever-changing learning landscape. The facilitator is a guide on this landscape and can provide some of conditions to explore, work and grow.
4. Introduction/Overview

The goal of this study is to capture my journey into conceptualizing and facilitating an inquiry-based learning (IBL) course as a complex adaptive system (CAS). This course will serve as a context for developing facilitator and student competence and capability, two concepts that comprise my understanding of resilience. As an action research study this work will aim to assist administrators and educators working in the investigator’s programme by offering a framework for conceptualizing IBL through the lens of Complexity.

The primary research question is: ‘How might educators conceptualize and facilitate an IBL environment as a CAS’? The study will focus on testing a series of propositions that I have developed. The propositions are statements about how a facilitator with complexivist sensibilities might approach key issues relevant to working in an IBL environment. These sensibilities are framed by the following qualities of complex phenomena from Davis & Sumara (2006):

1. Self-organized. Complex systems are formed by the actions of autonomous and interdependent agents;
2. Bottom-up Emergent. Complex systems exhibit properties that transcend the sum of individual agent qualities and do not rely on central organizing agents or structures;
3. Short-range Relationships. Information is exchanged locally between agents;
4. Nested Structure (or scale-free networks). Complex systems embed and are embedded within other systems that can also be considered complex.
5. Ambiguously Bounded – Complex systems are open systems because energy and matter exchange with the surrounding environment. As such, “judgments about their edges may require certain arbitrary impositions and necessary ignorances” (p. 5).
6. Organizationally Closed – Complex systems are coherent unto themselves and are considered closed to the extent that they maintain this coherence as energy and matter are exchanged
7. Structure Determined – Complex systems are adaptive because they can change their own structures in response to dynamic contexts
8. Far-from-equilibrium – Complex systems do not exist in balance with their surrounding environment

Davis & Sumara emphasize the inherent problem with this list because it does not discern between different cases and types of complexity. My conceptual framework will show I have come to discern complexity, but for the present purposes the propositions are based on the connections between these eights concepts and facilitating IBL.

The study of IBL, which will be described shortly, is concerned with the construction of knowledge, critical thinking and problem solving by groups of students vis-à-vis the generation and refinement of questions, information-gathering and evaluation, and communication. These activities are part of understanding the role of an IBL facilitator and I will frame them in context of the propositions.

My propositions will be evaluated in the context of an Inquiry course I currently facilitate at X University. I will produce a series of journals documenting my observations of the course. At the end of the course students will evaluate the course and my facilitation. After grades are assigned I will review the evaluations and any marker of a student’s identity will be removed or changed to protect it. Upon completion of this review, the student evaluations will be sent to external reviewers along with an account of the course written by the investigator. These reviewers will evaluate the extent to which my account and the student evaluations support or refute the propositions. An analysis of the reviewers’ findings will begin by comparing and contrasting it with my account. Areas of divergence and convergence in perspective will then be explored to produce a revised set of propositions.

5. Significance

Beyond it’s potential utility to the small group of educators working with the investigator, this work is significant in at least three different areas.

.1. Inquiry-based learning

IBL, in the context of the investigator’s teaching environment, is focused on the development of self-directed and lifelong learning skills. Dubbed the ‘Inquiry Skill Set’, the academic programme aims to develop the following throughout four years of a student’s tenure in the programme:

o time management
o posing a good question and refining it
o identifying sources of information
o critically evaluating and integrating information
o using information to answer a question
o communication in verbal, non-verbal and written contexts
o working with another person and a group
• identifying individual and group strengths and weaknesses
• dividing responsibility
• following through
• teaching and learning from each other
• giving and receiving constructing feedback
• dealing with minor conflict
o evaluating personal strengths and weaknesses in each area

There is currently a need in the inquiry literature to “determine which specific instructor behaviours and course elements have the greatest impact on student learning gains” (BHSc Programme, 2005). These learning gains include those listed in the Inquiry Skill Set. This work will be significant because it is aimed at developing a framework that will identify what those behaviours and elements look like from a particular perspective. The intent is not to examine IBL from the complexity perspective for the purposes of prescription or prediction because, as will be described later, a complexity perspective suggests strongly that it is neither desirable nor possible to prescribe behaviours or predict outcomes with much specificity. Rather, the goal is to articulate a general heuristic for working in an Inquiry environment and evaluate the utility of this heuristic in context of a course.

.2. Complexity Literature

Complexity science is a relatively new, growing, loosely-defined and encompassing field of study that is generally concerned with the patterns and relationships within and across systems of all types (both systems as phenomena and systems as specific fields of study). Complexity is moving from a phase of extreme enthusiasm into one of conceptual labour, requiring more integrity to understand how it can be used to productively yield insights and where the limits of applicability exist. At present, there has been a limited application of Complexity perspectives to understanding human learning in a higher education context. With exception to the growing body of research interrogating the relationship between Complexity and Education more generally, few studies have been conducted on a higher education course as a CAS. This study will be a significant contribution to specific educational research communities interested in Complexity because it will attempt to determine the extent to which concepts and methods from this ‘New Science’ are appropriate and useful for educators in IBL environments.

.3. Education Administration

A previous instructor of mine wrote recently:

Today, no less than yesterday, inquiry in the field [of education administration] seeks to amass empirical evidence with a view toward identifying allegedly better patterns and courses of administrative action which are thought to provide for ostensibly desirable organizational outcomes (Richmon, 2006, p. 8)

Richmon’s concern was that despite the recent influence of constructivism and critical theory, to highlight a few non-positivist perspectives, the fabric of education administration is still woven by an epistemological thread in which administrators do and organizations of people respond. He used the metaphor of Newton’s clock to describe the precision, predictability and linearity often sought by administrators seeking answers from research to implement in their schools.

I contend, as Richmon does, that social organizations behave as a CAS and that the field of education administration would be well served by thinking of administrative phenomena in terms of Complexity. My goal with this work is to prompt a shift towards a new way of thinking that sees teaching, just as much as administration, to be practices characterized by continual instability, non-linearity, and evolution. Although distinctly different practices with unique concerns, I believe this work will be significant in an administrative context because the skill set, processes and outcomes of Inquiry are reflected throughout all aspects of education. Because teaching, learning and administration are co-evolving systems of practice, I will argue that the study and practice of education administration can be fruitfully informed by the lessons learned in the Inquiry classroom (and vice-versa).

6. Literature Review

The literature relevant to conceptualizing education, facilitation and learning as Complex Adaptive Systems is broadly connect to theories of Complexity and Chaos, the conceptual underpinnings of CAS. These theories come primarily from the physical, biological and chemical sciences as well as mathematics (Gleick, 1987; Kauffman, 1995; Lorenz, 1993; Mandelbrot, 1983; Prigogine & Stengers, 1984; Wolfram, 2002). Complexity science is best described in terms of Complex Adaptive Systems (CAS) and has received some attention in social applications (Axelrod and Cohen, 1999; Buckley, 1998; Byrne, 1998; Casti, Brown & Eisenhardt, 1998; 1994; Ciliers, 1998; Clippinger, 1999; Kelly & Allison, 1998; Marion, 1999; McKelvey, 1999; Pascale et. al., 2000; Pascale, Millemann & Gioja, 2002; Stacey, 1996; Weick, 1996; 1997; Wheatley, 1999; Zimmerman, Lindberg & Plsek, 1998).

The growing branch of scholarship applying complexity sciences to education has, in a quick snapshot, focused on the application to school systems (Fullan 1993; 1999; 2001); classroom settings (Trygestad, 1997); cognition and teaching (Human-Vogel, 2005); higher education institutions (Cutright, 1996-7; 1999; 2001; Haggis, 2005; Shippengrover, 1996); curriculum and teaching (Davis & Simmt, 2003; Davis, Sumara, & Luce-Kapler 2000; Davis, Sumara & Kieren, 1996; Hunter & Benson, 1997); educational research (Davis & Sumara, 2006; Newman & Wessinger, 1993; Sawada & Caley, 1985); educational administration and planning (Griffins, Hart & Blair, 1991; Sungulia, 1990); teacher education (Davis & Sumara, 1997) and the philosophy of education (Frielick, 2005; Radford, 2005). This literature is quite diverse and highlights the multiple interpretations and applications of complexity and chaos theories. In the context of scholarship produced on teaching and learning in higher education, however, little attention is given to the implications of complexity science (cf. Axley & McMahon, 2006).

7. Theoretical Framework

The theoretical perspective through which this study is developed and analyzed is almost entirely concerned with complexity. Research undertaken through the complexity lens must consider what Richardson and Cilliers (cited in Davis & Sumara, 2006, p. 18) represent as the three broad schools of thought in complexity:

a) Hard (or Reductionist) Complexity – an approach usually taken by physicists that is consistent with analytic science which posits that the nature of reality is determined and determinable
b) Soft Complexity – an approach common in biological and social sciences which uses the metaphors and principles derived from the hard approach to interpret and describe living and social systems
c) Complexity Thinking – an approach concerned with the philosophical and practical consequences of seeing, thinking and acting in a world/universe assumed to be complex

This work is primarily concerned with how complexity thinking is applied to an IBL environment, although some reference to metaphors will be required to enable the reader and myself to think in terms of complexity. According to Davis and Sumara (2006), complexity thinking questions are oriented not by the “fact seeking ‘what is?’ nor the interpretation-seeking ‘what might be?’, but the practice-oriented ‘how should we act?’( p. 25). Truth from this perspective is concerned with adequacy and not optimality such that “in contrast to the demands for validity, reliability, rigour, and generalizability, complexity thinking is more oriented towards truths that are viable, reasonable, relevant and contingent” (p. 26).

From this perspective, there must be an acknowledgement than information is ‘compressed’ and ‘reduced’ by humans to make sense of their experiences. We must differentiate, interpret and generalize to cope with the vast information from the world around us at any given moment. Truth is thus considered as an interobjective claim:

“Rather than striving for an impossible objectivity, embracing a self-referencing subjectivity, or holding to a culture-bounded intersubjectivity, for the complexivist truth is more about interobjectivity. It is not just about the object, not just about the subject, and not just about social agreement. It is about holding all of these in dynamic, co-specifying, conversational relationships while locating them in a grander, more-than-human context.”(p. 15)

Central features of interobjectivity in complexity thinking are emergence and self-organization. Emergence, understood as the creation of novel entities and forms that transcend pre-existing forms, draws attention to relationship between the whole and it’s parts and the unfolding of forms and entities from within a system as a function of the relationship between the parts. In one educational research context, for example, consideration of emergence would focus on the transcendence of individual limitations in which groups of individuals create ‘grander cognitive entities’ that are not determinable as the sum of individual capacities (ibid, p.?). Self-organization is a process in which the order required for the viability of the system and the construction of emergent structures is created from within as a function of dynamic and critical relationships between the parts.

Any consideration of ‘knowing’ and ‘knowledge’ in this context often requires jumping between levels – e.g. individual, group, biological, cognitive, emotional, experiential, material, symbolic, cultural, and ecological levels. These levels are thought to be either enfolded within or from each other in a co-evolving web such that the complexity of the entire ‘system’ is the system itself and cannot be reduced.

The entire complexity of a system can never be determined because the researcher (or teacher, administrator, etc.) is both embedded within and co-evolving with the system being studied; as a researcher interacts with any of the aforementioned levels, the levels respond or change in some way, subsequently affecting the researcher and other levels. Stacey (2001), in speaking about the paradox of human agency, suggested complexity thinking is about understanding ‘enabling constraints’ - we are both enabled and constrained by these levels, how we interpret our world from a particular vantage point, and the co-evolutionary dance taking place across and within wholes and parts (levels). Complexity thinking research, therefore must consider the level of observation, the purpose of the observer and the dynamic between researcher and the phenomena being studied.

8. Conceptual Framework

This framework consists of four parts;
1. Resilience and Complex Adaptive Systems
2. Inquiry Based Learning
3. The Propositions
4. Stories

The first two parts outline the basic features underpinning the propositions and the fourth part, Stories, speaks to how the first three parts can be captured and studied.

.1. Resilience and Complex Adaptive Systems

The building of this framework starts with issues of educating for competence and capability, two terms that have particular meanings. Capability came out of the United Kingdom over twenty years ago in response to the need for “increasing organizational competitiveness and the rapid changes in the nature of work” (Hase & Davis, 1999). It is defined by Cairns (2000) as “…having justified confidence in your ability to take appropriate and effective action to formulate and solve problems in both familiar and unfamiliar and changing settings”. It is “an all-round human quality, an integration of knowledge, skills and personal qualities”. Capable people know how to direct their own learning, work well with others and can apply themselves in both novel and familiar situations (Hase & Kenyon, 2000).

Capability is compared to competency and is defined by Cairns (2000) as “individual and measurable skills demonstrated and assessed against agreed standards of competence”. According to Velde (1999) and Mulcahy (2000), educating for competency has tended to result from economic and social changes as it focuses on abilities to perform specific tasks and roles in the workplace. The problem, Wildman (1996) said, is that “competencies tend to be prescriptive and are designed for a more stable environment with familiar problems” (p. 86). That is, competencies are concerned with known and predictable contexts and not the messy, unknown, complex, and unpredictable reality of the interaction between a person and the world around them. Although competencies may be a part of capability, unpredictability and variability present challenges to educating students solely or primarily for competence (Phelps et. al.)

Greenhalgh and Fraser (2006) situated these concepts in the following graph adapted from the work of Stacey (1996).

(Figure from Greenhalgh & Fraser, 2006)

agreement - the degree of agreement on what constitutes "the truth"
certainty - the degree to which outcomes can be predicted

They contended that learning takes place in the ‘zone of complexity’, a fuzzy area between capability and competence. I use the concept of resilience - the ability of a living system to sense out and adapt dynamically to changing circumstances – as the point of contact between competence and capability. Learning is thought of in terms of the adaptation that occurs in complex adaptive systems (CAS). The study of CASs deal with nonlinear systems that can adapt to changing environments and are characterized by the capacity to self-organize in non-equilibrium environments (a system not in equilibrium with it’s surrounding environment). Living organisms, societies, sports teams, ant hills, economies and the human nervous system, among many other systems, are examples of CASs. My previous work (Park, Keshet, & Harnish, 2006) outlines the following ten features common to CASs:

1. Agents and parts have autonomy and interdependency and act based upon local conditions and referential knowledge
2. Agents can self-assemble with minimum specifications
3. CASs are embedded within other CASs
4. Control is decentralized throughout the system

5. Organization and complexity emerges from the relationships between the agents and parts

6. Exhibit self-similarity across levels

7. Exhibit non-linear behaviour

8. Sensitive to initial conditions and diversity in the system

9. Trajectories and patterns are affected by historical dependence, feedback and experience

10. Have legitimate and shadow subsystems

Putting these features together, I can describe how adaptation occurs through changes to referential knowledge, the minimum specifications, relationships between agents, and self-organization at the edge of chaos. The edge of chaos is where CASs are the most adaptive to internal and external changes and is characterized by a tension between what a system ‘knows’ (competency) and the ability to respond to new contexts (capability). Inquiry-Based Learning (IBL) will be conceptualized throughout this work as ‘education in the zone of complexity’ and ‘learning at the edge of chaos’. My propositions will aim to make connections between features of IBL and CAS and the study will test their adequacy. Before I set out this framework, I need to outline a few more features of IBL.

.2. Inquiry-Based Learning

IBL is an approach to teaching that has become a prominent feature in undergraduate course offerings in the Health Sciences. As an educational approach, it is closely related to Problem-based Learning (PBL), arguably beginning with Socrates, but most attributable to educational developments at McMaster University Medical School, Hamilton, Canada in the 1960s. PBL and IBL both use students’ prior knowledge to understand and structure new knowledge and the context of real-life situations/problems to make the transfer of knowledge between the problem and real-life more likely. The structuring of new knowledge is brought about by discussion, asking and answering questions, peer teaching and critiquing (Biley and Smith, 1998). According to Mangussen et. al (2000) and Feletti (1993), IBL is more holistic and flexible than PBL, less dependent on using specific clinical problems, can make better use of systems theories, and can provide a wide variety of learning methods to accommodate a diversity student learning styles.

The IBL educator is considered a facilitator of learning, a concept very different than teacher. Malcolm Knowles (1975) captured quite well the requirements of this kind of facilitator:

“It required that I focus on what was happening to the students rather than on what I was doing. It required that I divest myself of the protective shield of an authority figure and expose myself as me, an authentic human being, with feelings, hopes, aspirations, insecurities, worries, strengths and weaknesses. It required that I extricate myself from the compulsion to pose as an expert who had mastered any given body of content and, instead, join my students honestly as a continuing co-learner”.

The facilitator is not a ‘directive lecturer’. Students must determine their own learning objectives, how to meet those objectives, identify their own ‘knowledge deficiencies’ and evaluate what they have learned. The facilitator is also not a ‘wallflower’. According to Neville (1999), facilitators can serve a number of functions that include acting as a resource, setting classroom climate, assistance with the framing learning objectives, and giving feedback. These functions are achieved primarily by asking questions that probe, critique or lead students to construct knowledge in context of the questions they are asking themselves. IBL facilitators, I will argue, are in the zone of complexity because they neither abandon students to an unstructured environment (low certainty, low agreement) nor dictate what they must learn (high certainty, high agreement).

The IBL educator, who is interacting with students in the context of an academic program, may also be a teacher and an evaluator in addition to being a facilitator. Teachers are typically considered ‘knowledgeable’ (sometimes ‘experts’) in a particular field of study and traditionally ‘impart’ this knowledge to students. When a PBL discussion between students is dealing with basic conceptual issues in the facilitator’s area of expertise, the facilitator may step in “to correct basic misconceptions that might be leading individuals (or the group as a whole) astray” (Neville, 1999, p. 396). According to the Silver and Wilkerson (1991) study cited by Neville, questions of how and when to step in appear to be highly contestable issues in the literature partly because facilitators with ‘expertise’ are more likely to direct tutorials, speak more frequently and longer, and answer questions more directly compared to ‘non-experts’. These findings call into question the harm that expertise can have on developing self-directed learning skills.

The role of a facilitator’s knowledge in an IBL context, however, is not as central to a student’s learning. It is often peripheral and always contingent. The outcome of IBL is not to master a specific body of knowledge that someone, for example, might want to learn for diagnosing diabetes as a physician in a variety of contexts. The outcome is for students to create knowledge through the pursuit and refinement of questions and to develop self-directed learning, group, and communication skills along the way. The facilitator’s role is to hold them accountable to agreed-upon objectives. This accountability is perhaps one of the most complex and problematic issues in IBL. Some IBL facilitators are empowered to assign grades and both facilitators and students bring have a diversity of conceptions and motivations about performance for grades. In some contexts grades are negotiated with students. In this negotiation, students and facilitators can draw from peer and self-evaluation as well as observations of performance over the course to evaluate the extent to which the course objectives were or were not met.

.3. The Propositions

It is undeniable that a classroom of people qualifies as a complex adaptive system in itself and, consequently, is subject to the same operating features as other living systems. The question is whether an instructor wants to consciously explore and exploit its CAS features or rely on more traditional educational methods (and, of course, the possibility, or probability, of a combination of both). This implies working in harmony with—facilitating—CAS processes as opposed to attempting to suppress and, thereby, in some ways antagonizing natural processes and people, as mechanistic methods often do.
(Axley & Cohen, 2006)






Figure – IBL Facilitator Zone of Complexity

1. Look at facilitation through the lens of complexity

The above framework identifies the competence and capability of the facilitator in terms relationships between tasks and environments that are known, unknown but knownable, and unknowable. These three categories reflect the spectrum the degree of agreement and certainty attributable to the task and environment in questions.

I propose that we can think of competence of the facilitator as known variables and would include the facilitator’s frame of reference and the roles the will play (their past experience as facilitator/teacher/evaluator), knowledge of objectives for the course, knowledge of where and when interactions might occur, and the local conditions of the learning environment (ie. location and setup of classroom, online milieu). In these contexts, the facilitator makes perceptions of the task or environment at hand and can readily categorize and respond. Competence is not fixed and can co-evolve over time. As it is engaged in new contexts it may both change those contexts and be changed by the contexts. In this way, what is considered ‘known’ can change as the facilitator learns through the other two domains.

We can consider capability in terms of unknown variables and deals with how facilitators function in highly uncertain situations and where it is not possible to predict and plan future outcomes with much specificity. Capability would include responding to ‘crisis’ events, such as students in distress or a disruption to the class, allowing for and responding to emergent outcomes (ie. students combining questions and concepts in novel ways), learning from engaging competence in new contexts, working with non-linear approaches to assessment (ie. narratives and concept maps), asking questions that aim to stimulate creative thinking. Capability requires facilitators to first take action followed by perceiving events as they unfold to inform the next steps.

Somewhere between competence and capability are tasks, environments or variables that are unspecified or unknown, but depending on how the facilitator is interacting with the students, may become more specified/known. Facilitators can engage students in ways that bring students’ past history, experiences, and preconceptions to the surface, identifies the embedded systems that influence the context for learning (ie. personal challenges, peer group, family life), reveals patterns in student behaviour, and where role boundaries might exist between student and facilitator.

2. Connect course and agent interactions to embedded systems

Knowledge of local context, past history, and referential knowledge are important for understanding the systems that agents are embedded in and how those agents are relating and adapting. What meaning do these concepts have for building competence and capability in IBL environment? I propose that the facilitator, in designing, facilitating, and evaluating, considers:

• Understanding local contexts of learning – the individuals in the room, what concurrent courses and/or experiences are going on beyond the classroom, the time of day, the year and programme the students are in, classroom setup
• Being sensitive to global/local relationships – events and dynamics beyond the immediate local environment have the potential to impact local conditions
• Honouring referential knowledge and past history – the perceptions that students and facilitators bring from previous experiences, the context and story of those experiences (academic, family, peers, etc.)
• Working with co-evolving relationships – the behaviour of students and facilitators as well as the unfolding of the course can both affect and be affected by changes in these embedded systems

3. Set conditions for self-organization with minimum specifications for learning

Order and organization in CASs cannot be imposed externally from a ‘master agent’ nor can it be programmed through a master plan. Under certain conditions people are able to self-assemble into coherent, self-sustaining collectives by vis-à-vis the process of self-organization. Self-organization requires that a sufficient quantity and diversity of people are interacting for order to arise. Diversity can be understood in terms of the different sense-making capacities of the people involved and interactions as the norms, rules, or heuristics influencing what interactions between people are possible or likely.

IBL facilitators can set conditions for self-organization by setting the ‘minimum specifications’ for learning. ‘Min Specs’ are the basic conditions that must be met in order for a system to self-organize. Specifications limit or define the possible interactions and setting more than Min Specs can compromise the ability of systems to self-organize. In the context of the course, they can be communicated as the minimum expectations of the course, roles of the facilitator, and the responsibilities of the student. The programme I facilitate in sets the development of the following skills as responsibilities for students:

a. time management
b. posing a good question and refining it
c. identifying sources of information
d. critically evaluating and integrating information
e. using information to answer a question
f. communication in verbal, non-verbal and written contexts
g. working with another person and a group
i. identifying individual and group strengths and weaknesses
ii. dividing responsibility
iii. following through
iv. teaching and learning from each other
v. giving and receiving constructing feedback
vi. dealing with minor conflict
h. evaluating personal strengths and weaknesses in each area

In addition to min specs, self-organization requires space and time for interaction. Formal meeting times in a classroom are sufficient, but not always necessary as students can meet on their own time outside of classroom or in online environments if those possibilities exist.

4. Enable interactions that produce coherence and incoherence

Coherence is defined as state of a CAS in which meaning is shared among agents, internal tension is reduced, actions and patterns of actions are consistent with other parts of the CAS and a minimum amount of energy is dissipated in internal interactions (Eoyang, 2004). Facilitators can enable the emergence of coherence in an IBL environment in ways different than setting conditions for self-organization. Coherence may be enabled by;

• Designing activities or asking questions that help students get to know each other (group ‘bonding’)

• Asking students about issues, concepts and group dynamics they are having difficulty with and addressing them with the class or in smaller groups

• Helping the class or small groups set their own ‘norms’

Incoherence can occur in the context of significant difference, described by Eoyang (2004) as “a distinction within a system that establishes a potentially generative tension, which represents the potential for change”(p. 11). Incoherence can be enabled, for example, by:

A. Asking wicked questions

According to Zimmerman et al. (1999):

“A question is 'wicked' if there is an embedded paradox or tension in the question. The embedded tension or paradox is an opportunity to tune to the edge of chaos. Their value lies in their capacity to open up options, inquiry and surface the fundamental issues that need to be addressed…The paradoxes or tensions are often found in the implicit assumptions we hold about a context, issue or person. Exposing these assumptions in a question is often both uncomfortable and a relief. It is uncomfortable because the myths we create to bury our assumptions often seem more acceptable and defensible.”

B . Working with Silence

There is a tendency for some members of a group, including facilitators, to ‘fill in’ the silence that comes about in a group discussion with ideas and questions. Allowing for silence can produce tension in the classroom because direction is not suggested. People need time to think and new directions to emerge.

5. Encourage the emergence of complex forms (displays of competence and capability) by balancing the generation of internal diversity with ‘chunking’

In the context of CASs, Pascale, Millemann, and Gioja (2000) posited that:

The survival of any system depends on its capacity to cultivate (not just tolerate) variety in its internal structure. Failure to do so with will result in an inability to cope successfully with variety when it is introduced from an external source. (p. 20).

Creative processes enable the generation of diverse forms. When people are stuck, facilitators can ask questions aimed at opening up possibilities – ie. Are there other options? What would happen if you changed the conditions/questions? What would you do in this situation? What do you think this group of people would say?

After creative processes, such as brainstorming, a large number of possibilities can be overwhelming. The use of ‘chunking’, which involves experimenting with small pieces first, helps build complex systems form and evolve by starting small and growing from what works. As pieces begin to work, they can be linked together and produce new possibilities (Zimmerman, et al). Facilitators might ask; of all the possibilities, which are the most critical to understanding your questions? How might the possibilities relate to each other?

6. Build in feedback loops and allow other loops to self-organize

Enabling coherence/incoherence and the emergence of complex forms requires multiple feedback loops. Finding the way forward in uncertain environments requires continual sensing of the environment, however, the inability to step outside of one’s own shoes necessitates information from other agents in the system.
Facilitators can aide in the creation of feedback loops by:

• Asking students to determine the feedback they need
• Benchmarking – snapshot of performance at beginning and end of course
• Making observations, not judgments
• Outside perspectives
• Formal self-evaluation
• Formal peer-evaluation

Visible and hidden feedback loops can emerge within the class or small groups unpredictably. Facilitators can ask students how these loops affect their perceptions of self and other.

8. Assist students in creating the criteria and format for evaluation through the lens of complexity with ‘stories’

Facilitators can help students (groups and individuals) to evaluate their own learning in the context of capturing resilience. As agents in the system with a unique perspective, facilitators are also evaluators and so the criteria and format should emerge from a dialogue between students and between students and facilitators. The Min Specs for evaluating the learning of a CAS could focus on the following five approaches to evaluating CAS environments developed in one of my recent works (Park, Keshet, & Harnish, 2006).

• Changing what is foreground and background. If understanding our environments as CASs involves looking at local interactions and patterns of relationships between people, what we see as foreground and background should be reversed. This involves looking at knowledge, not as something that exists in people’s minds, but also between people within the context of interaction.

• Looking for disjunctures and convergences between ideas and actions. Capra (1996) and Lee (1997) advance that to better understand interdependencies, we need to look for where ideas and actions succeed or fail at intersecting. This suggests that it is necessary to describe actions in the context of agents’ mental models. Referring back to the discussion on the properties of CASs, mental models concern the local conditions and referential knowledge of agents. Both properties help to establish the meanings agents attach to their actions and could help explain disjunctures and convergences between ideas and actions

• Looking for unexpected events and how people and interactions change in the face of uncertainty. The hallmark of CASs rest in their non-linearity. This means that cause and effect linkages may not be good at describing the behaviour of the system because small events can perturb into large ones and vice-versa. Some of the time, or perhaps even most of the time, people may be expected to behave in certain ways, but during periods of instability for example, general models and trends aren’t very useful. If we seek to understand how an organization responds to change, an indicator of it’s ‘fitness’, we should look to unexpected events to see how people react and relationships change in the face of uncertainty.

• Looking for dynamics, processes, and patterns across levels and how they change. The ways in which people are expected or thought to interact can be found in formal documents and policies outlining role expectations, however, it is the de facto interactions that are the key indicators of system dynamics. The shadow subsystem, or the informal interactions taking place between agents, demonstrates the self-organizing and emergent properties that come from “spontaneously occurring organizational events, structures, processes, groups, and leadership that occur outside of officially sanctioned channels” (Goldstein, 1999, p. 65). Looking for patterns that highlight reoccurring events, the dynamics of how people respond to change help to understand what processes are keeping the system coherent or are constraining new behaviours from taking foot. Because of nesting and self-similarity, patterns may be a function of patterns occurring at other levels of the system. Additionally, the system’s history is important and understanding how yesterday’s outputs become the inputs of today illustrates the role of feedback mechanisms, how patterns evolve over time, and how the system responds to unexpected events.

• Observing how the role of the facilitator is affecting the system. By accepting that the facilitator affects and is affected by the system, the reflexive and interactive role of the facilitator can be used to enhance an understanding of system dynamics. By examining how students are affected by the facilitator, the facilitator can also gain additional understandings of how the system responds to feedback.

.4. Stories

Critical to understanding how, for example, students might use feedback, documentation and other information from the course to evaluate their learning, is how agents in CASs make what Weick (1995) termed sensemaking. Armentrout-Brazee (2002) highlighted Weick’s perspective that sensemaking experiences needed to be captured and communicated by:

something that preserves plausibility and coherence, something that is reasonable and memorable, something that embodies past experience and expectations, something that resonates with other people, something that can be constructed retrospectively but can also be used prospectively, something that captures both feeling and thought, something that allows for embellishment to fit current oddities, something that is fun to construct. In short, what is necessary in sensemaking is a good story. (Weick, 1995, p. 60-61 in Armentrout-Brazee)

In her dissertation on organizational stories and narratives as CASs, Armentrout-Brazee presented a compelling framework for using stories to understand learning and organizations - “as complex adaptive systems, stories convey connections and relationships between variables through the organizing process used by the storyteller and the audience” (p. 43). This framework, which forms the second component of my conceptual framework, was developed by Armentrout-Brazee, who articulated how stories:

1. Demonstrate interdependence and embeddedness. Stories are connected to other stories in their substance and processes of construction and telling.
2. Are dynamic with the possibility for multiple interpretations. Depending on who the storyteller and audience is, as well as the context in which the story is told, stories can have multiple meanings.
3. Capture complexity via their nonlinearity. Stories can capture context and dynamics through a variety of literary devices such as dialogue, plot, character, and setting over periods of time.
4. Possess the ability to adapt. Stories can be adapted to the context in which they are told and can adapt over time as new meanings are made or as a consequence of interaction with other stories.
5. Are self-organizing systems. Order and meaning come about as a story is constructed and as a result of the interaction between storyteller and audience.
6. Require simple rules. These simple rules, which Fisher (1984) discussed as part of ‘narrative rationality’, require that stories be capable of “capturing the experience of the world, simultaneously appealing to the various senses, to reason and emotion, to intellect and imagination, and to fact and value” (Fisher, 1984, p. 15).

The ‘simple rules’, Armentrout-Brazee highlighted, are probability and fidelity, which are determined by the listener and concern how free of contradictions the story is and the degree to which it rings true with experience of listener. This connects well with complexity thinking, which is concerned with adequacy and reasonableness. Connelly and Clandinin advanced the work of a number of authors and offered a number of concepts to consider in narrative as part of their metaphorical three-dimensional inquiry space (Connelly & Clandinin, 2000, p. 50). They first consider Dewey (1938), who proposed that the two criterions of experiences are continuity and interaction. Continuity refers to the idea that experiences arise from previous experiences and lead to further experiences. This idea can also be reframed as temporality (past, present, and future). Interaction can be described in terms of personal, or inward, interactions and social, or outward interactions. The third dimension is Place, which are the situations, contexts or physical spaces that inform the other two dimensions. According to Connelly and Clandidin, “using this set of terms, any particular [narrative] inquiry is defined by this three-dimensional space [of continuity, interaction and place]”.

9. Methodology

I will be employing an action research methodology in this study because it is a way of “’complexifying’ the relationship among researchers and research situations so that the boundaries between these are blurred” (Davis & Sumara, 1997, p. 301). According to Phelps (2005), action research is both theoretically compatible to the study of complexity and education and a “methodology that supports complexity-based teaching practice.”(p. 38). This method will involve the collection of data in three steps:

1. Facilitator narrative developed from reflective journals
2. Responses from former students
3. Responses from six scholar-educators

.1. Justification and Description of Methodology

Phelps and Hase (2002) offer the most salient account of complexity as a basis for action research and show how it is suitable for:
a. acknowledging the open, non-linearity of social systems
b. the emergent nature of change
c. change as self-organised adaptation
d. the role of agent interaction
e. inherent unpredictability and sensitivity to initial conditions
f. capturing the role of feedback, system stability
g. mixed method approaches

The purpose of action research is to create change in dynamic and complex systems, which involves the input of energy through action to prompt a system into a state of non-equilibrium. This involves “testing out hypotheses ‘on the run’” (ibid, p. 511) and looking for how disequilibrium states lead to new opportunities. Second, because agents in CAS act in terms of ‘internal models of schemas’, action research can acknowledge and encourage participants to challenge the assumptions of these models. This is a way of “introducing ‘noise’ and actively promoting disequilibrium” (p. 513) and “challenges individuals to reflect on new ideas, concepts and theories and to engage in action aimed toward change” (p. 515). Third, generalisability is something that “rests in the hands of those who participate or read about the study, rather than in the study itself” and makes participants and researcher(s) collaborators in knowledge production (p. 514). Finally, action research is part of a cycle of inquiry and Dick (2000) sees it an approach “where if sources agree then the researcher searches for exceptions in the next cycle. If they disagree then the researcher searches for explanations” within the present cycle (p. 517).

.2. Data Collection
.1. Facilitator narrative developed from reflective journals

A narrative will be created from an Inquiry course I currently facilitate at a university in Southern Ontario. During the course I will produce a series of written reflective journals that document my observations of the course. Through my journaling I will produce an account of the class week by week, the intent behind my actions and how I respond to classroom dynamics, what I see going on between students, what they are struggling with and what they are accomplishing. My goal is to piece together a narrative of the course from beginning to end with attention given to how my propositions were embedded into my facilitation and the course dynamics.

According to Phelps (2005), written reflective journaling “provides scope not only for gathering research data but also for fostering and assessing learning in ways that are congruent with complexity theories” (p. 39). The co-construction of knowledge that takes place in action research can be captured in a practical way with reflective journals that allow for understanding to emergence vis-à-vis a dialogue between students, teachers and researchers (Phelps, 2005). Other advantages include capturing ‘reflective insights’, the history and initial conditions of the system, and introducing ‘noise’ to prompt change and dissonance.

.2. Responses from former students

Because knowledge from a complexity perspective is understood to be inter-objective, one should consider the interpretation from other perspectives. As such, I must go beyond my own interpretations and consider those of the students and responses will be solicited from them after the course has finished and grades submitted. An evaluation form will be handed out to students asking them to evaluate the course in context of the propositions (see Form A in Appendix). After I leave the room, they will form the three groups of six students they have been accustomed to working in all term, move to a computer lab to complete the evaluation online and email the file to the programme’s administrative assistant. I will ask this assistant to ensure that I cannot access the files nor have privy to the identity of the sender. The students will be asked to ensure that neither individual identities nor the group’s identity is indicated on any of the electronic evaluation forms. I will request the files from the programme office and remove any indicators of identity if they are present.

.3. Responses from six scholar-educators

Being inter-objective means engaging perspectives from multiple levels and an ‘outside the system’ is critical to understanding how those outside the classroom interpret the application of complexity by facilitators and students. I will engage six scholar-educators with the following three documents (see Form B in Appendix); a short description of my thesis that outlines the rationale for the study and the propositions, a narrative that accounts for my perspective on applying these propositions to the classroom, and the student responses. I will ask the participants to review the documentation, make comment within the documents themselves, and have a one-hour discussion in context of three questions (see Form C in Appendix for description of instructions and questions). I will take notes during the discussions.

.3. Analysis

The aim of having scholar-educators evaluate the propositions in context of their own expertise, the narrative, and the student responses is to bring about emergent forms that arise as new meanings and new questions to engage in a subsequent research process.
I will orient my analysis of emergent forms under four broad categories developed in one of my recent works (Park, Keshet, & Harnish, to be published).

• Looking for disjunctures and convergences between ideas and actions. Capra (1996) and Lee (1997) advance that to better understand interdependencies, we need to look for where ideas and actions succeed or fail at intersecting. Mental models concern the local conditions and referential knowledge of agents and both properties help to establish the meanings agents attach to their actions and could help explain disjunctures and convergences between ideas and actions.

• Looking for unexpected events and how people and interactions change in the face of uncertainty. The hallmark of CASs rest in their non-linearity. This means that cause and effect linkages may not be good at describing the behaviour of the system because small events can perturb into large ones and vice-versa. If we seek to understand how an organization responds to change, an indicator of it’s ‘fitness’, we should look to unexpected events to see how people react and relationships change in the face of uncertainty.

• Looking for dynamics, processes, and patterns across levels and how they change. Looking for patterns that highlight reoccurring events, the dynamics of how people respond to change help to understand what processes are keeping the system coherent or are constraining new behaviours from taking foot. Patterns may be a function of patterns occurring at other levels of the system and looking at the system’s history is important to see how feedback mechanisms influence the development of patterns and how the system responds to unexpected events.

• Observing how the role of the researcher is affecting the system. By accepting that the researcher affects and is affected by the system, the reflexive and interactive role of the researcher can be used to enhance an understanding of system dynamics. By examining how participants are affected by the researcher, the researcher can also gain additional understandings of how the system responds to feedback.

I will use the data grouped in these sections to create a revised list of propositions and a strategy for communicating my findings because of time and space constraints. I will have to make decisions as to how I want to revise the propositions and, where appropriate, will articulate my arguments for making revisions and identify problems that cannot be resolved.

.4. Participants

Because of the limitations of doing a Master’s thesis, I only aim to have six participants. I intend for at least three of the participants to be scholar-educators in complexity theory and education. The application of complexity theory is so broad that scholarship and teaching/facilitating with an understanding between complexity and education is critical. The three I have in mind are faculty at Canadian universities. Two of them have written extensively on the application of complexity to education and administration and their work has significantly influenced the development of the course I facilitate and this thesis. The other is a curriculum-unit planner for an Ontario medical school is currently enrolled in a complexity theory PhD programme in the UK. These three individuals are familiar with my background and have stated that they would appreciate a formal opportunity to engage with my work. There are other scholar-educators in the field that could be deemed ‘eligible’ for participation, however, I am not aware of the extent to which they may be able to critique the propositions. In the event that these scholar-educators do not agree to participate in the study, I will make a call for research participants through two complexity and education listservs. The criteria for participation is a background in complexity evidenced by publications and/or conference presentations and demonstrable experience applying complexity to educational settings.

The other three participants must be scholar-educators in IBL. Experience with literature and in the classroom is critical to offer insightful perspective on my propositions and the evidence. Two potential participants I would like to approach have published research on IBL. One of these participants works as a facilitator in my programme and can act as an internal reference point on IBL as it is conceived within the programme. The other has an extensive IBL facilitation background beyond the programme and runs a number of courses concurrent to my own. He can act as a reference point for the particular cohort I work with because he has some familiarity with the IBL background these students have. It is possible that both scholar-educators have worked with some of the students in my course, however they will not be able to ascribe identity to student evaluations as the forms will be electronic versions with identifying markers removed and they will be completed by small groups (not individuals). The third potential participant I would like to approach is grounded in PBL, a form of IBL and his perspective on issues of competence and capability, through the lens of a medical education, will provide a unique perspective on the CAS-IBL relationship. I have these three in mind because I have a pre-existing relationship with them that can assist the development of this work. They are familiar with the context in which I teach (the programme) and have expressed interest in better understanding the relationship between complexity and IBL. In the case that these scholar-educators do not agree to participate in the study, I will make a call for research participants within the IBL ‘community’ at my university. The requirement for participation is experience teaching an Inquiry course.

.5. Recruitment

All potential participants will initially be approached by e-mail with a short description of the research study to determine their interest in participation (Form A in Appendix). When participants have agreed to participate, they will be sent the Informed Consent form for completion (Form B in Appendix).

.6. Risks and Benefits

Participants may benefit from reflecting on and discussing their experiences with either IBL and/or complexity and education. Participants may also benefit from looking at issues of complexity in education from a novel perspective and contribute towards the development of that perspective. I do not believe that there are any risks as a result of your participation in this study.

.7. Privacy and Confidentiality

The anonymity of people involved in this research is ensured as well as the confidentiality of the information given. Members of the participant’s institution, OISE/UT nor any other group or institution will not know which participants have contributed to the study and no identifiable information will be provided in the written report. With the exception of my thesis supervisor John Portelli and my second reader, the raw data will not be shared with anyone without the participant’s permission. All raw data will be kept on file in a secure filing cabinet and on my computer for five years after the completion of the project and then will be destroyed. Furthermore, I may publish the results of the study and give talks about the study at presentations or conferences.

.8. Compensation

No compensation will be given for participation.

.9. Conflicts of Interest

There are no conflicts of interest to declare.

10. Analysis

The aim of having scholar-educators evaluate the propositions in context of their own expertise, the narrative, and the student evaluations is to start a critical dialogue. The critical element I hope to receive from these scholar educators will challenge me to question my own notions of Inquiry, facilitating, educating for resilience and complexity thinking. Their responses and critiques will be analyzed as part of a process of self-evaluation and it is this self-evaluation that I want to make an explicit part of this work. Although one goal of this work is to ‘test’ the propositions, the overall goal of understanding resilience would be missed if this testing was not seen in context of a fallible facilitator co-evolving through his experience and through a dialogue. As such, I want to focus on emergent forms that arise through new meanings and new questions.
These emergent forms are crucial to understanding the possibilities of the concept of dialogue in critical dialogue.

I will have to limit my analysis of emergent forms to creating a revised list of propositions because of time and space constraints. Based upon my narrative, student evaluations and the scholar-educator perspectives, I will have to make decisions as to how I want to revise the propositions and, where appropriate, will articulate my arguments for making revisions and identify problems that cannot be resolved. The revisions will be guided with my overall assumption that Inquiry is a critical dialogue that occurs in the zone of complexity and to make a case for educating for resilience, I need to explore how the relationships responsible for the manifestation of competence and capability are connected to facilitating with complexity thinking. This assumption may also come into question and be revised.

I will orient my analysis of emergent forms under four broad categories developed in one of my recent works (Park, Keshet, & Harnish, to be published).

i. Looking for disjunctures and convergences between ideas and actions. Capra (1996) and Lee (1997) advance that to better understand interdependencies, we need to look for where ideas and actions succeed or fail at intersecting. Mental models concern the local conditions and referential knowledge of agents and both properties help to establish the meanings agents attach to their actions and could help explain disjunctures and convergences between ideas and actions.

ii. Looking for unexpected events and how people and interactions change in the face of uncertainty. The hallmark of CASs rest in their non-linearity. This means that cause and effect linkages may not be good at describing the behaviour of the system because small events can perturb into large ones and vice-versa. If we seek to understand how an organization responds to change, an indicator of it’s ‘fitness’, we should look to unexpected events to see how people react and relationships change in the face of uncertainty.

iii. Looking for dynamics, processes, and patterns across levels and how they change. Looking for patterns that highlight reoccurring events, the dynamics of how people respond to change help to understand what processes are keeping the system coherent or are constraining new behaviours from taking foot. Patterns may be a function of patterns occurring at other levels of the system and looking at the system’s history is important to see how feedback mechanisms influence the development of patterns and how the system responds to unexpected events.

iv. Observing how the role of the researcher is affecting the system. By accepting that the researcher affects and is affected by the system, the reflexive and interactive role of the researcher can be used to enhance an understanding of system dynamics. By examining how participants are affected by the researcher, the researcher can also gain additional understandings of how the system responds to feedback.

I will use the data grouped in these sections to create a revised list of propositions and a strategy for communicating my findings because of time and space constraints. I will have to make decisions as to how I want to revise the propositions and, where appropriate, will articulate my arguments for making revisions and identify problems that cannot be resolved.


11. Timeline

January 16 – finish facilitator narrative
January 18 – organize student responses
January 23 – finish propositions section
February 1 – have package ready for participants
February 2 – send out packages to participants
March 30 – aim to have all participants feedback
April 15-30 – data analysis completed
May 15 – conclusions and implications
June 1 – first draft completed


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