Personal Blogs

• How is leadership distributed?

there are predesigned levels of leadership here, all positional. There is the federation, then the principle and the English department head. we are not given any information on teachers, i assume they are not included in this scheme.

• Who is accountable?

eventually the federation. but at the present time, practically it was first the department head (left) and the principal (overruled).

• At what point do those with positional leadership roles feel that they should intervene and why do they do so?

they intervened at the point that the school (and the leadership of the school) may not be able to deal with the situation effectively, by its own resources. but i rather think that there is something unfair in this entire scheme. the principal had sought for help and resources (a new English department chief) but was not provided with. so the leadership of the federation actually failed to create the environment and resources for the perceived (by the school) change.

This article present a very open and contemporary approach to learning, in that students and  teachers take the responsibility of learning collaboratively, to the extent that teachers may as well be called as 'learning advisers'. i understand the concept and do believe that this is a good idea. but still, two questions remain:

1. can this frame be defined as one of 'distributed leadership'? the main discussion in the article is rather based on the ownership of learning, i.e., distributing ownership to an overarching community that encompasses not only policy makers and school administrations but also individual teachers and learners (students). in this regard, i'd rather think that the frame described is one of transformative leadership exercised by the policy makers and administrations, and teachers and learners alike are delegated to become 'agents' of this transformation.
2. it is not clear that this approach would indeed be beneficial in all stages of learning, that is, from K-12 to undergraduate to postgraduate education alike. it is probably a very good idea for postgraduate learning (my own context) in which learners may actually own and  lead their individual learning by virtue of their backgrounds but may not be as good an idea in primary schools in which, as also demonstrated in this article, the role defined for learners would rather be one of improving their learning within a predefined context. again, it becomes agency rather than leadership.

so in summary, it is either me or the authors who are confused about the definition of leadership. 

Here we go, my personal study and career plans:

To fınısh EE811 and graduate

to be an educational leader in surgical education (SE)

This activity call for the identification of the 'relevant professional leadership development or professional/competency framework' for my own context. i did some research on this, as i do not work in a pure educational context. the closest i could get is this definition of educational leadership by AOSpine, an academic organization (an NGO) for which i had been doing some volunteer surgeon training, and it goes like this:

"(Leaders are) distinguished members of the worldwide spine community, who have demonstrated a sustained and significant contribution to educational excellence in the field of spine surgery."

• where you currently place yourself as a professional within this structure
  

this definition was provided to describe the efforts of educators who were awarded the title 'regional educator of the year (2016)', a title which had been awarded to me in the previous year. supposedly then, i had been recognised as one of these leaders by this organization as well. does this mean that i had been a real educational leader? well, hard to tell, for two reasons:

1. excellence is very hard to define, it is mostly used (here as well) undenotational, mostly signifying hard work.
2. i have certain doubts on whether doing your job (albeit as a volunteer) is the only quality on which leadership should be based upon.

• which elements required for leadership within your work context do you hope will be supported and strengthened by studying this module?
  

my expectation on the most important element to be supported and strengthened from this module is the understanding of and subsequently the ability to create a change in my educational context. i do understand that this ability is not the sine-qua-non aspect of leadership, but still, in an educational environment that is rapidly changing, i would like to get some insight about the mechanisms by which to propel all the stakeholders to a common goal of 'state of the art education'.

Reflecting on the ROMA framework

in this exercise I shall analyse two obstacles for effective implementation of learning analytics (LA) that had been identified in the previous week; existing organizational culture (OC) and quality of analytical data (QAD), using the ROMA framework as suggested.

The ROMA framework:

1.     Define a clear set of overarching policy objectives

a.     OC: it is clear that changing the existing culture in any context may be extremely difficult and may take a long time. in this regard, the policy I’d like to adapt is to create a need and urgency within the organization in order to facilitate a much easier and expedited adoption of LA.

b.     QAD: this is somewhat associated with the policy objectives above, but not exactly. increasing the quality of data can only be realized through adoption of higher quality research projects. this is expected to be a long and painstaking process. on the other hand, it is necessary because;

                                               i.     it is the only real way to map the context accurately, and

                                             ii.     higher quality data may make the paradigm shift in OC easier.

2.     Map the context

a.     OC:

                                               i.     clear definitions of what we have (for our purposes, as LA)

                                             ii.     clear definitions of what we may have, or what we want to have

                                            iii.     why should we have them, and why is it urgent?

b.     QAD:

                                               i.     clear definition of our open research questions

                                             ii.     analysis of the quality of analytical data currently available

                                            iii.     analysis of the disparity between what is available and what is required.

3.     Identify the key stakeholders

a.     OC:

                                               i.     Managers, directors, policy makers

                                             ii.     Teachers, teachers’ associations

                                            iii.     students, students’ associations and advocates

                                            iv.     IT and software producers

b.     QAD:

                                               i.     Managers, directors, policy makers

                                             ii.     Teachers, teachers’ associations

                                            iii.     Research organizations (Universities, NGOs), researchers

                                            iv.     funding organizations

                                              v.     academic societies, publishers, meeting organizers etc.

4.     Identify learning analytics purposes

a.     OC:

                                               i.     develop metrics to be used for quality improvement steps (in education)

                                             ii.     develop a better understanding of our educational ecosystem

                                            iii.     gathering evidence on our advantages and disadvantages, rights and wrongs

                                            iv.     gaining competitive advantage (everybody else has it!)

b.     QAD:

                                               i.     gathering, filtering and sorting data for higher quality research

5.     Develop a strategy

a.     OC: Steps:

                                               i.     clear delineation of the need and its urgency

                                             ii.     identifying priorities in LA, what do we need data on?

                                            iii.     developing the methodology

                                            iv.     addressing and convincing the practitioners at the field (i.e., teachers) on the need and urgency

                                              v.     developing human resources for LA

b.     QAD: Steps:

                                               i.     clear delineation of the need and its urgency

                                             ii.     identifying priorities in research, what do we need answers for?

                                            iii.     deciding on the methodology

                                            iv.     addressing and convincing the practitioners at the field (i.e., teachers) on the need and urgency

                                              v.     establishing resources for sustainable funding

                                            vi.     developing human resources for research

                                           vii.     dissemination of research results

6.     Analyze capacity; develop human resources

a.     OC:

                                               i.     analysis of whether our organization

1.     wants to change (even at times of evident urgency)

2.     can be changed (internal dynamics)

                                             ii.     analysis of human resources:

1.     are the policy makers convinced?

2.     do we have the buy off of the practitioners in the field?

3.     do we have an effective IT system and staff?

b.     QAD:

                                               i.     analysis of whether:

1.     we have open research questions

2.     we want to be involved in research (it is expensive and time and effort consuming)

3.     we have an existing research culture

                                             ii.     analysis of resources:

1.     are the policy makers convinced?

2.     do we have personnel experienced in planning and conducting research?

3.     do we have the buy off of the practitioners in the field?

4.     do we have an effective IT system and staff?

7.     Develop a monitoring and learning system (evaluation)

a.     for both (OC and QAD):

                                               i.     what are the outcome measures

                                             ii.     the quality of data and analysis, do they warrant policies built upon them?

                                            iii.     are we ready to (re)change?

types of data collected by academic (university) libraries:

• demographics: including age, gender, ethnicity, address etc.
• socio-economic status: including family income, loans, bursaries, etc.
• academic level and achievements: year, GPA, credits, etc.
• curricular activities: conferences, projects, exhibits etc.
• social and extracurricular activities: all that involve swiping the same card, faculty store, sports, cultural events, etc.
• previous library activity
• VLE activity.

five ways these may be used to support analytics that could lead to the improvement of learning and/or teaching:

1. identifying at-risk learners (not using the library in some disciplines is an at-risk sign per se) and offering/providing support.
2. identifying the trends in learning/research performed through the library. which topics are in more demand? should we recommend the department chair to establish a section on, say, 'Learning Analytics'?
3. identifying issues with the physical structuring of the library and re-designing the space accordingly. which sections are mostly used? which are not used at all?
4. in connection with #3, using library as a promotion/marketing tool. which tools in library are more relevant for our pedagogy? are we being successful in promoting them? what can be done to this end? would it be ethical?
5. identifying trends in library use. why does it decline? should we try to re-vitalize physical attendance? what other services can we provide? to which target audiences?

from the innovations listed and discussed in the 2016 report on 'Innovating Pedagogy' by OU, three may definitely be associated with analytics. Here is my list and reasons:

1. Epistemic cognition: this innovation may not seem to be one that would benefit from data but in fact, it is very much dependent on data (or, evidence). an analogy here can be the concept of evidence based medicine which had been gaining more and more traction in practices and training of medical personnel. common tools (although still imperfect) are the systematic reviews of literature and meta analyses which aim to compile a very wide range of data from very wide ranges of sources, languages, and evidence levels and present compact conclusions based on these data sets. thereby, the learners (readers) are granted with the ability to get acquainted with the entire range of available data, its quality and when possible, conclusions or recommendations based on it. this methodology needs to be applied to all categories of knowledge, especially to social sciences in which robust data sets are scarce, with the potential exception of sociology, working on large surveys (even in sociology though, random sampling is the enemy of big data analysis). so, in essence, although i don't propose that we can measure epistemic cognition through analytics, i propose that we need analytics for epistemic cognition.
2. Immersive learning (IM): as defined in the article, IM pretty much refers to applications of virtual reality (VR) into, especially, vocational training. vocational training may probably be the hardest field in education in regards to learning analytics. expanding the dental school example in the article, we may use data based on the exit examinations of dental schools (comparing these students in IM programs with others) but as for training 'better' dentists, we shall eventually need to define parameters in these professionals practices (such as patient satisfaction rates, complication rates, infection rates etc.) (which is already implemented by the NHS in UK and several insurance companies in US) and use analytics to see whether these parameters get better with IM. on the other facet of IM, big data on real life procedures is essential for developing reliable VR models. this is where analytics (not necessarily learning analytics) is definitely needed.
3. Citizen science: can be a very fertile source of data. the collaborative efforts that may be defined as citizen science are, by definition, on the virtual space and each and every one are potentially traceable. the discussion here might be on the methodology to be used to promote participation and to measure its impact. i can visualize an Amazon (or Netflix) type of promotion in which social network users demonstrating any slightest interest in sciences (STEM mostly, but could be any) are softly introduced and encouraged to participate in citizen science by targeted ads and suggestions. metrics in K12 may be based on standardized examinations (such as PISA), but may be virtually impossible in adults. i couldn't even think of a way to develop metrics for adults involved in citizen science.

Week 10 of H817, dedicated mostly to MOOCs have introduced us to the concept that they may be typed as (x) and (c), which stand for behaviorist and cognitivist vs connectivist. Here we are a week later, faced with the challenge of re-structuring our OER based courses of several weeks ago into a connectivist approach. 

Acknowledging a high potential of political incorrectness, i tend to think that some educational contexts may be more amenable to be structured as (c)s than others and fortunately enough, the OER based T4T (training for trainers) course i have tried to construct in week 8 is one good example as it allows for the unlimited use of connectivist principles of 'model and demonstrate' for teachers and 'practice and reflect' for learners. A counter example here though would be teaching (learning) anatomy to (as) a surgeon; it is good to know-where the knowledge is, but this is of no practical use if it is not readily present and recallable from within your brain. so i am more in line with the second proposition of Bill Kerr here (in Downes 2007) when he states "Either the new theory is intended to replace older theories... Or, the new theory is intended to complement older theories". Connectivism, to my understanding may be an excellent approach to enhance learning the foundation of which has been laid down using other pedagogies.

now, back to the task after this gibberish. here is how i would restructure my course:

How does  ds106 compare to Coursera and like in terms of technology, pedagogy and philosophy? interesting question; they are so different to the extent of deterring any comparison but here is a try:

1. Technology: the technologies used and required are not necessarily radically different in context, but rather in extent. ds106 requires a very higher level of ICT literacy from its participants. they have to establish themselves a virtual (optional) identity and space and communicate with each other using various technologies (mainly blogs). the participant needs to be very familiar of the virtual domain as well as online communications. Coursera and like on the other hand rely on more humble technological requirements, which may vary depending on the course you are taking but the essentials are just a computer and a reasonable internet connection. 
2. Pedagogy: very different approaches here. based on the discussions on MOOCs we have read this week, Coursera may be a standard example of an xMOOC based on the behavioral/cognitive theories whereas the ds106 is an excellent example of a cMOOC based on connectivism. the former offers structured courses with pre-determined content delivered by a tutor whereas the latter has no official syllabus and relies on the content created and provided by the learners themselves, without even a facilitator. this does not necessarily mean that one is better than the other though, just that one or the other may be more applicable to certain contexts and situations. as an example, it may be almost impossible to run a ds106 like course for surgical training, a field in which creativity is actively discouraged.
3. General approach and philosophy: this is closely related to differences in pedagogy. in summary, ds106 assumes the learners are willing to take the ownership of their learning, create PLEs and eventually, self-learn. other(s) however do not have such assumptions other that taking a person's own enrollment in a given course as a token of a desire to learn. the rest is pretty much mediated by the platform and tutor(s).

As i have iterated above, these differences do not necessarily signify a hierarchy in any sense, they are just different approaches to learning/teaching with different areas of applicability.

I would suggest the 3 key issues in OER as:

1. Performance: Although there is some evidence that the performance of OER is (to say the least) akin or even better than that of non-OER, what is available as evidence is not conclusive. The core difficulty in this regard stems from problems in developing specific metrics and assessment strategies. Quizzes, as proposed to overcome this issue remain to be crude methods of summative assessment which may not necessarily translate to the actual performance of the OER and/or their end users. I have to admit that I do not, have an educated guess on how this problem may be addressed at a global scale apart from a wait and compare policy, i,e,. comparing the performance of OER with those of non-OER in the longer run. Methodology for performance assessment would still need to be developed.
2. Finances: This is an argument that has been ongoing for some time. Do OER offer better financial solutions for the learning and education of end-users, be they teachers or students. Considering the face value, there shouldn't be an argument. OER, by definition are open, hence free. The argument on the other hand may arise from the necessity of using technological intermediaries to reach these resources, like computers (of any kind) or broadband internet access. Therefore, there is a chance that we are actually substituting one expense (eg. textbooks) with another (eg, laptops). The solution to this will most probably be offered by the increasing ubiquity of technologies, bringing their rices down substantially (as opposed to substantial increases in the prices of copyrighted ER such as textbooks).
3. Access: As discussed above access remains to be the decisive issue in OER. Apart from the expenses associated with it, in some underserved regions, it may not be available at all due to technological and/or political problems. The bottomline here is; if you don't have internet access you cannot make use of OER, regardless of their cost. Efforts directed at creating a global (free) internet cloud, available at almost all regions throughout the world may overcome this problem.

Consider each of the questions below and log your reflections in your learning journal/blog.

On the basis of your own experience:

·      Do you sense that your innovations (as supporters of learning) have been valued, encouraged, supported?

I have this sense of being valued, encouraged and supported in some contexts (mostly commercial) but not in others (mostly non-profit). What is happening is probably  that the for profit organizations are more akin to see innovations in education (or, for that matter, in any subject) as opportunities and new fields of entrepreneurship. I assume these organizations do realise and recognise that what I call an innovation may not be; a) a real innovation, but rather a variation of what others have been doing, and b) even if it is, it may not prove to be applicable on a larger scale, sustainable or profitable. But these are pretty much inherent in the concept of entrepreneurship, there will be risks.

Non-profits (be them public medical schools or private non-profit foundations) on the other hand, when confronted with the same situation are far more reluctant to take these risks. Further, it may not only be a matter of taking risks but rather a resistance to adapt to a new culture, which may be active or passive.

·      What evidence do you have to support your view?

Petersen (2014) argues that for educational entrepreneurs, innovation yields higher returns based on the examples of 3 entrepreneurs who have succeed in establishing innovative start-ups and managed to grow them to extents of being taken over by larger companies, yielding large profits. This is not the very concept that we are discussing here, but still, this may be a major motivation for innovation.

On the other side of the spectrum, Bateman and Davies (2014) issue a warning on the unpredictability of the development of computer-based learning technologies whereas Eva and Anderson (2011) on the uncertainties of the innovativeness of innovative educational ideas/projects.

A personal example may be the implementation of a Problem Based Learning (PBL) system in the public medical school in which I was faculty some 15 years ago. The concept was brought into the attention of the faculty pool by the Dean and was broadly discussed in circles of volunteers before implementation. When it was suddenly started at the beginning of an educational year though, it was seen that:

1.     Educational background of the faculty pool was not at the level required for PBL,

2.     Commitment from the faculty pool was virtually non-existent, as they had not been presented with any incentive to buy in,

3.     Most interestingly, there was a totally unexpected resistance from the student body the majority of whom had clearly stated that this system was way too demanding for them and they would rather go back to the lecturing format.

As far as I know, this school still claims to provide a curriculum based on PBL but in reality it has been converted back to ‘lecturing in small groups’ due to the passive resistance from the faculty and students alike.

From the perspective of your context:

·      How widespread is innovation in your organisation?

At the present time, I work with several NGOs (academic societies, foundations, some medical product companies) which have developed and pursue individual educational programs, as faculty member and/or as a committee member. Based on this, I can say that, as a concept, all these organisations are in full support of innovation in education. We sometimes spend days discussing how to develop and implement innovative methods and technologies. The result? We are yet to see any real innovations (such as and specifically, OER) being adapted.

·      Are there policies or statements that relate to innovation? If yes, how are they implemented?

I am not aware of any official policies in this regard.

·      What implications, if any, does this have for your attitude towards innovation?

I have to say that this reluctance actually increases my appetite for developing and using innovative technologies. In fact, I have recently partnered with a fellow surgeon to start a company that would develop software infrastructure for educational organisations (which I have listed above) in their efforts to convert to new educational methods and technologies. I remain to be optimistic, in a sense.

References:

Bateman J and Davies D, (2014) The challenge of disruptive innovation in learning

Technology. Medical Education 48, 258-33

Eva KW, and Anderson MB (2011) Lessons learned through innovation in medical

Education. Medical Education 45, 434-5

Petersen JL, (2014). For education entrepreneurs, innovation yields high returns. Education Next, Spring 2014, 9-16. Available at: www.educationnext.org, Accessed on: Feb 14, 2018