from data to endgame for dissertation and theses: what does it take

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Exploiting Rapid Change in Technology Enhanced Learning … for Post Graduate Education From Data to Endgame What does it take?

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Page 1: From data to endgame for dissertation and theses: what does it take

Exploiting Rapid Change in Technology

Enhanced Learning

… for Post Graduate Education

From Data to Endgame – What does it take?

Page 2: From data to endgame for dissertation and theses: what does it take

Students Experience the Endgame differently

I like being near the top of a mountain. One can't get

lost here. Wislawa Szymborska

When you're passionate about something, you want it

to be all it can be. But in the endgame of life, I

fundamentally believe the key to happiness is letting

go of that idea of perfection. Debra Messing

If there's not any endgame, we're in quicksand. We

take one more step, and we're still there, and there's

no way out. Richard Shelby

Page 3: From data to endgame for dissertation and theses: what does it take

Agenda

1. Endgame backwards – qualitative2. Endgame backwards – quantitative3. What they have in common – the beginning of a map

through from data to the end

Dissertations discussed today from PQDT Open.

Page 4: From data to endgame for dissertation and theses: what does it take

The Documents – both from Stanford

Large scale empirical (2009)

• 212 pages

• 6 chapters – used #3 for theory

• 50 pages of tables at the end

Grounded Theory (2008)

• 440 pages

• 8 chapters – 3 for 3 different dimensions of the results then 7 for a model and 8 for conclusion

Page 5: From data to endgame for dissertation and theses: what does it take

Study #1

Page 6: From data to endgame for dissertation and theses: what does it take

AbstractCognitive flexibility: The adaptive reality of concrete organization change

by Furr, Nathan R., Ph.D., Stanford University, 2009, 201; 3382938

Abstract (Summary)

The question of why some organizations change when others do not is of central interest to

the organization change literature. While large-scale, empirical studies have emphasized

organization demographic characteristics such as size, age and resources, a recent body of

case-based literature has begun to emphasize the role of cognition in determining whether

organizations change. In particular, the literature suggests that organizations characterized

by cognitive flexibility are more likely to change than those characterized by cognitive rigidity.

This study investigates the impact of three core constructs that contribute to cognitive

flexibility—variety, novelty, and framing—on when organizations change their technology. I

examine the impact of these three constructs at both the team and organization level on the

likelihood of three degrees of technical change: major, moderate, and minor. I find that all

three constructs: variety, novelty, and framing contribute to technology change. Furthermore,

I find that the greater the scale of change, the greater the impact of cognitive flexibility on

change. Finally, I investigate the link between change and performance, and find that, in fact,

large changes actually improve performance more than small changes but only after an

initial adjustment delay.

Page 7: From data to endgame for dissertation and theses: what does it take

How Much Data Was Collected?

Pilot interviews (12) 1 hour each – analyzed whether the questions made sense… - yes they did so he progressed.

The study – public and private data on the PV industry from 1992 – 2007Data from Venture Xpert, Dept of Energy and Renewable Energy Lab – (70 lists total) Data was filled in by interviews (4)Data measured in quarterly intervals – all changes in technology recorded in public documentation

Page 8: From data to endgame for dissertation and theses: what does it take

How Was It Analyzed?The analysis conducted as part of this study consists of three parts. First, conducted a pilot inductive study in which he validated the research question. Second, he conducted a deductive analysis to statistically test the effects of cognitive flexibility on change. As part of this analysis, he also tested the effects of change on performance.Third, to more robustly illustrate the statistical analysis he constructed three cases of organizations from the sample that illustrate the change process

Dependent variable change – major, moderate, minorIndependent variables – team experience, (career histories were extracted from biographies on the web) science or business – who came and who went in each company each quarter?

Page 9: From data to endgame for dissertation and theses: what does it take

Other Things MeasuredStructure varietyTechnical noveltyOutward opportunity

Measured it all through content analysisTexts were scored on whether motives for change were economic vs sustainability and then commercial vs technical

Statistical analysis on cognitive flexibility and change and on effect of change on performance through correlations and descriptive statistics.

Page 10: From data to endgame for dissertation and theses: what does it take

Where did he get to in the end?Additional exploratory analysis of CEO’s – as to their adaptive flexibility and what

that meant for their organizations.

The results suggest that CEO-level cognitive flexibility does impact change

although the management team as a whole has a greater impact on change than

the CEO alone, particularly for large changes

And then this requires the results are gone through carefully for each level of change etc.

Page 11: From data to endgame for dissertation and theses: what does it take

Study #2

Page 12: From data to endgame for dissertation and theses: what does it take

AbstractBest practices of outstanding mentors in psychology: An ecological, relational, and

multicultural model

by Chan, Anne, Ph.D., Stanford University, 2008, 430; 3313810

Abstract (Summary)Recent studies have pinpointed disconcerting trends regarding the recruitment, retention, and graduation rates of ethnic

minorities in doctoral programs. Mentoring has been touted as part of the strategy to address this problem. However, there

is a paucity of research on the mentoring of ethnic minorities in academia, particularly with regard to how mentors tackle

cross-cultural differences in mentoring relationships. This dissertation addresses this gap in the literature by examining the

practices of outstanding mentors in cross-cultural mentoring relationships. The sample consisted of 9 mentors nominated for

being outstanding mentors and 17 doctoral-level psychology protégés—all the mentoring relationships diverged along racial

and/or cultural lines. Grounded theory was used in this study to uncover mentor practices as well as to discern a theory of

cross-cultural mentoring. Data was collected from semi-structured interviews with mentors and their proteges, audiotapes of

two actual mentoring sessions, as well as archival materials such as e-mail exchanges.

The data showed that the mentors engaged in a wide variety of practices targeted at three key areas: individual career

development of the protégés, relationship/trust building, and socialization/organizational development of the protégés.

These mentor practices were found to address the special concerns and challenges faced by ethnic minority and culturally

different protégés.

This dissertation contributes to the literature on mentoring by proposing an ecological model of mentoring that emphasizes

the contextual, relational, and multicultural nature of cross-cultural mentoring relationships. The findings from this study

contribute to our understanding of the processes within a mentoring relationship and the ways in which mentors can

successfully negotiate differences.

Page 13: From data to endgame for dissertation and theses: what does it take

How Much Data Was Collected?

Grounded theory – requirement for looking at evidence from several angles in order to build theory26 participants, in depth interviews over 9 monthsDocument analysis as well: emails, between mentors andprotégé’sAudio taped sessions (2) were also analyzed

Pilot done to verify ideas – opened ideas about mentor access that were key at the end

Page 14: From data to endgame for dissertation and theses: what does it take

How Was It Analyzed?

Triangulation, negative case analysis, member checking, Reflexive journaling, reactivityMultiple readings of data and examination over the courseof collection – analysis throughoutField Notes and memos: observational notes, theoretical notes, methodological notes, and open and selective codingConstant comparison of previous ideas to new ones, reflecting back, integrating categories, delimiting theoretical options, then writing theory

Page 15: From data to endgame for dissertation and theses: what does it take

Constructing similarities and

differences in order to propose a map

through from data to the end

Page 16: From data to endgame for dissertation and theses: what does it take

Process comparison

#1

• Purpose to extend what is known with broad question: When do organizations change?

• Lit set up dimensions and levels

• Results in one chapter - 2 dimensions discussed each across3 levels of change

• Outcomes across each of 3 types of literature

#2

Both had LOTS of data and complex system for analysis

Similarities:

1. Both had complex system to discuss results across a number of dimensions

• RQ to be answered

• Lit set up the dimensions

• Each dimension became its own results chapter (= 200 pages)

• Outcomes results taken together- amodel for cross-cultural mentoring

Page 17: From data to endgame for dissertation and theses: what does it take

Where #1 get to in the end?The descriptive statistics suggest that entrepreneurial organizations are in fact

highly adaptive. The frequency of technical change suggests that change inside

entrepreneurial organizations is a central feature of early organizational life.

When do organizations change?1. Cognitive flexibility influences whether /how much2. That is true at multiple levels within organization3. CF has a different effect depending on size of change –

more the bigger it is4. Change improved performance overall

Page 18: From data to endgame for dissertation and theses: what does it take

Where #2 get to in the end?Model for mentoring…

The major mentor functions identified in this model are:

• Building trust in the mentoring relationship

• Building community and supportive networks

• Providing access to the inside story

• Providing validation

• Providing support for career development

• Providing protection

Each conceptualized across individual, relationship, and organizational

contexts

Page 19: From data to endgame for dissertation and theses: what does it take

http://pqdtopen.proquest.com/search.html

Suggested Map for those with DataWhat might these comparisons suggest to others?

1. Lit sets up the sort mechanism for your data2. Questions determine where you want to end up

3. Steps might include:1. Beginning, during, after analysis sort, sort, sort your ideas into

the different strata determined throught the lit.2. Keep asking – how do these ideas answer my questions?3. Keep journal of the progress so you can go back and double

check.4. Use models from others – as your ideas progress search again.

Page 20: From data to endgame for dissertation and theses: what does it take

What’s Up at DoctoralNet?Continuing development in two areas: 1) Support, 2) Non Academic career

tracks and transferable skills

Webinars

Opt-ins For SummerTrack your milestones

30 day challenges – writing and work/life balance

Top 10 motivations

April 11th Read/Listen/Comment Reading Group https://www.bigmarker.com/doctoralnet/Copy-of-Read-Listen-

Comment-Academic-Writing-Help

April 13th Critical Analysis Part 1 with exercise https://www.bigmarker.com/doctoralnet/Critical-analysis-part-one-with-

exercise

April 18th Preparing for your Final Defense/VIVA https://www.bigmarker.com/doctoralnet/Preparing-for-your-Final-

Defence-VIVA

April 18th Lingerers Group: Picking up the pace on literature

work

https://www.bigmarker.com/doctoralnet/Lingerers-Second-Quarter-2-

2017-Picking-up-the-pace

April 20th Critical analysis part two from exercise https://www.bigmarker.com/doctoralnet/Critical-analysis-part-two-from-

exercise

April 24th IRB/Ethics: Ins, Outs, What to do and What to

avoid

https://www.bigmarker.com/doctoralnet/IRB-Ethics-Ins-Outs-What-to-do-

and-What-to-avoid