League for Innovation STEM tech Denver, 2014

1. Fiancés! Gauging engagement 4 ways
Katherine Watson, Coastline Distance Learning, Fountain Valley, CA Bizarrissime@gmail.com
1 | P a g e
Abstract:
Commitment, engagement, motivation, and success are frequently proposed as measures of
student, program, and institutional “achievement” in higher education. Rigorous, replicable,
objective scientific analysis is typically not applied to quantify any of these four notions,
however. Rather, it is “fuzzy concepts” that are called upon to explain and/or evaluate them
subjectively. And yet, institutions of all kinds can advance most effectively when they exhibit
something objective, something measurable and definite that can serve as a framework from
which they may marry and metamorphose. In twenty-first century education, such a framework
ought to be applicable institution-wide, across disciplines, and around the world. It can comprise
a Learning Paradigm of the sort that was honed in the US in the mid-1990’s and that might be
adapted to twenty-first century students and their needs.
Introduction:
Definitions of educational commitment, student engagement and motivation, and academic
success often incorporate vague, subjective, fuzzy-science perceptions such as feelings,
satisfaction, trust, and the like. And so-called “measurements” of these four concepts typically
include terms such as “frequent”, “likely”, “manifold”, “strong”, “unlikely”, or “weak.” But notions
that may at first seem impenetrably subjective can in fact be analyzed objectively. Three ways
are proposed below to render objective what may appear to be only subjective: First, currently
popular “fuzzy” concepts, often using “fuzzy science”, must be seen for what they are;
“commitment”, “engagement”, “motivation”, and “success” represent exemplars of fuzz. It must
be asked if/how these concepts can be considered for more rigorous analysis. Second, these
four concepts can be placed in diverse disciplinary and cultural contexts for comparative
scrutiny; for instance, they are used commonly in communications, education, psychology,
marketing and business. And third, and finally, a renewed, objectively realizable Learning
Paradigm can be offered to guide educators toward clarity. Indeed, it will be questioned how the
goals inherent in the Paradigm can be ensured objectively with respect to commitment,
engagement, motivation, and success.
Fuzzy concepts and fuzzy science: Inexactitude in an era increasingly exact
“Fuzzy concepts” typify the subjective, the inexact. Rather than depending upon numbers or the
precision of statistics, they emanate from, and often exploit, the inexact emotional. Words such
as “happy”, “satisfactory”, or “pleasurable” mark the fuzzy. In a similar vein, “fuzzy science”
comprises the intellectual outlook that things occur “to a certain degree or extent”, “with some
magnitude of likelihood”, rather than with a certain probability ranging from 0 to 1. Zadeh (1997)
proposed that people communicate knowledge more commonly than not through the use of
“fuzzy concepts”, rather than otherwise, implying that the “fuzzy” has proven ever more
prevalent and important as machines have become increasingly responsive to human input.
Zadeh has continued by stating that “the (soft) social sciences, including economics,
psychology, philosophy, linguistics, politics, sociology, and religion, among others… (should
have) picked up on their own use of (the fuzzy).” But although the “fuzzy” may be useful to
promote feel-good, non-threatening interaction, and it may even provoke “meaningful” reactions,

2. it remains typically inexact, requiring distinctions, conditions, or qualifiers. Sociolinguists, among
others, point out that the “fuzzy” is best clarified through recognition of social, ethnic,
philosophical, religious, and linguistic constructs that “frame” the fuzz. And psychologists hold
that the strict binary logic gates that define “sharp” or “hard” computer reasoning do not
characterize the often illogical, but meaningful, “softer” associative patterns of the necessarily
fuzzy human mind. We are human, and our very nature is characterized by fuzz, in this analysis.
Indeed, the very human-oriented field of nursing offers a good example of the meeting of fuzzy
and sharp, of soft and hard. Koshar (2014) outlines certain distinctions defining both modes of
reasoning: On the one hand, the “exact” or “hard sciences” are acontextual, deductive,
empirical, objective, quantitative, reductionistic, and values-free; on the other hand, the fuzzy
“soft sciences” are contextual, inductive, qualitative, subjective, and values-influenced. Nurses
know, in Koshar’s understanding, that it is not the case that fuzzy and sharp represent a zero-sum
2 | P a g e
mind game in mankind.
What follows is a presentation of four fuzzy terms used frequently in education, along with
definitions of the terms from various academic and non-academic fields in the United States and
elsewhere. Subsequently, a renewed version of Barr and Tagg’s Learning Paradigm will be
proposed to promote discussion, bringing focus to the fuzz.
The four terms are: Commitment, engagement, motivation, and success.
Commitment, seen for what it is and may be contextually
Commitment implies “follow-through”, as United Kingdom business communication guru James
Manktelow (2009) states, adding that it involves a taking on of personal responsibility;
commitment is best developed, in this analysis, through communication, which is the interactive
process par excellence of promoting human understanding.
In education, commitment is frequently equated with persistence or attrition, with the latter being
an absence of the former. Given this reckoning, it becomes easy to measure commitment by
determining how many students leave class, leave school, leave academics altogether. But at
least two questions arise when such an equation is proposed: For one, is commitment really just
obstinate doggedness under a different name? And, secondly, should we not dig more deeply to
find out the sources, the causes, and the consequences of failed commitment? For their part, for
instance, Hackman and Dysinger (1970) have stated, with respect to the second question, that
students who fail to commit do so for any one of four fuzzily undefined reasons: financial
difficulties, academic problems, family trouble, and social problems. These reasons can be
classed as “fuzzy” because, although survey and questionnaire data are reported, the data
depend upon “perceptions”, “optimism”, and things subjectively “favorable” or not.
Interestingly, educators in the Usa often retain a definition of commitment with an emphasis
different from that of professionals in other countries. Thus, as John Hanson (2012) has written
for the American Association for Supervision and Curriculum Development (ASCD), the term
promotes for Americans the kind of Horatio Alger air of rugged determination discussed by
Hackman and Dysinger, a praiseworthy diligence, “with a visible symbol in effort,” typically
among students more than among teachers. By contrast, the Australian Northern Territory

3. Government and the New Zealand Ministry of Education, among others, see commitment as
flowing from education professionals, including teachers, administrators, and all other staff, to
students. Besides subject matter competence, a continuing desire to meet student needs, an
incessant striving to improve, and an active interaction with colleagues mark the commitment
that must first infuse the educator before he can stimulate the student, in this view. Indeed, the
New Zealand Te Ke Ipurangi holds that educational professionals are the critical key to
commitment; we must “have an unremitting focus on student learning.” The “personal
responsibility” cited by the aforementioned Manktelow is therefore the province of the professor
initially; students are encouraged to take it on through a sort of subtle professorial push.
An even broader-based, or –sourced, responsibility for developing commitment has been
proposed in northern Africa’s informatics-based Observatoire sur les Systèmes d’Information,
les Réseaux, et les Inforoutes au Sénégal (OSIRIS), as set forth by that organization’s secretary
general, Olivier Sagna (2005). Sagna holds that commitment to the achievement of educational
goals must, like commitment in any/all other public domains, flow naturally from a nation’s
political will, as that is nurtured by its business sector, itself having a vested interest in proper
schooling so that diplomas or academic certification will lead to rewarding jobs. Sagna points
out that, as countries throughout the world accept that commitment is as political as it is social
and educational, international transdisciplinary development will move apace.
In western Europe, Robert Michit (2008), of the University of Grenoble-centered European
Laboratory of Social Sciences and Human Resources, has noted that commitment will probably
always remain difficult to measure objectively, since it basically comprises things “psycho-social”,
and is thus anchored in subjectively sensed “social determinants”, including the
aforementioned political ones; commitment involves the interaction of individual social position,
the social environment, and the position of one’s society as it is engaged in the wider world. The
“objectification” of such commitment requires rational thought, Michit continues, and a setting
forth of clear, group-accepted measurable definitions of terms, alongside discussion of people’s
shared understanding of their engagement with those terms.
3 | P a g e
Engagement, seen and contextualized
Although the two American English words “commitment” and “engagement” are defined in many
other languages by a single word, or at least by words synonymous with one another, student
engagement in the United States, as Change magazine has reported, “…has come to refer to
how involved or interested students appear to be in their learning and how ‘connected’ they are
to their classes, their institutions, and each other.” That is, academic engagement comprises
something more than the pure communication or the taking on of responsibility that inhere in the
English term commitment, as set forth above. Educational consultant and “service learning”
expert Adam Fletcher (2011), of Olympia, Washington (Usa) has described engagement in
school as “a student’s willingness, need, desire, and compulsion to participate in, and be
successful in, the learning process.” Notably, Fletcher adds that “there is little consensus among
students and educators as to how to define (engagement).”
Like many social scientific concepts, then, engagement remains a fuzzy one. “Positive
emotional tone” is cited, along with “intense efforts and concentration” and “enthusiasm,
optimism, curiosity, and interest.” Typically, these descriptors are difficult to define precisely and

4. are even more difficult to measure. They express the sort of thing that we can recognize when it
is there but that we cannot share.
A 2007 report made by the American Association of Colleges and Universities (AACU) held that
engagement could be “enhanced” by educators’ concerning themselves and their students
across disciplines with “the Big Questions”, exemplified, according to the AACU, by examining:
how to accommodate international culture(s) and values; how to realize global interdependence
and how to address it; how to adapt to the changing economy worldwide; and how to achieve
and maintain human dignity and freedom.
And in Canada, Parsons and Taylor, of the University of Alberta “University Partners”, published
a review of the literature on student engagement in 2011, stating that the phenomenon is
“ubiquitous in our school systems, but not yet understood.” The review adds that “there are
several types/categories” of engagement, including: “academic, cognitive, intellectual,
institutional, emotional, behavioral, social, psychological, to name a few”. The review goes on to
say that there is much “murkiness” to the meaning of any of these, and that “interesting
qualitative criteria and differing definitions of engagement in learning” exist. Indeed, the
Canadian report continues, “the question of measure(ing) the process and not simply the
content of learning” must be addressed during any analysis of engagement, if only because, as
the University Partners found, as has also been noted with respect to commitment, there is “a
gap between what teachers consider engagement in learning and what students consider
engagement in learning” (2001:04).
Indeed, as Jay (2012) has written, engagement is becoming ever more often a “public”, a
“community” affair, in part because of AACU-style notions of transdisciplinary and trans-national
“interdependence” and also in part because of the increasingly “social” and/or “interactive”
nature of news, if not knowledge as a whole. Jay suggests that, like Fletcher’s “service
learning”, curricula of “project-based engaged learning”, once the province of vocational-technical
schools or more recently that of STEM programs alone, have “revitalized” academic
programs in the arts and humanities by “integrating (them) into public life,” often making them
accessible openly through multiple media. As Sénégal’s Oliver Sagna proposed in 2005 in his
push for an “engaged” e-Sénégal, three “poles”, or objectives, are becoming increasingly easy
to attain in a world where physical boundaries are dissolving and where technological access to
anything is becoming almost overwhelming: (1) To put citizens and their enterprises (small
business, particularly) at the center of their governments’ plans and preoccupations; (2) To
permit and to facilitate access among all sectors of society to education, training, and
information; (3) To respond to the needs expressed by various service providers and decision-makers,
so as to promote productive and responsive decision-making. Thus, for Sagna,
governmental commitment can and should lead to business and school engagement for an
educated, internationally developed society in all sectors.
But how is engagement to be measured? Hardy and Bryson, of the United Kingdom’s Higher
Education Academy (2012) report research results from the UK, Canada, Australia, Singapore,
and the United States—all Anglophone societies--that “engagement is positively related to
persistence rates and grades”, as well as to “measurable study behaviours”, such as “level of
academic challenge”, “enriching educational experiences,” a “supportive academic
environment”, “active and collaborative learning,” and “student-faculty interaction”. In Australia in
4 | P a g e

5. particular, Hardy and Bryson write, engagement is demonstrated by students’ active and
effective access to work; that is, their engagement is clear when they can show that they have
been able to apply their classroom-learned knowledge to an outside-the-classroom job. But,
these authors stress, it remains the “feelings” of the student that are most important
determinants of engagement, and these feelings are not only something “holistic” that suffuses
the engaged student, but they also remain fuzzy in the conceptual sense, difficult to define
objectively or to measure.
Grasgreen (2013) reports that more than 500 institutions, mostly in the United States,
responding to an Inside Higher Ed query on engagement have typically cited students’ access
to and use of academic advisers and/or counseling as handy, easily-calculable measures of
engagement. Grasgreen adds that within the past four years, however, measures of
engagement have become broader-based and more easily calculable, including questions to
students about how many and what kinds of E-mail interactions they have had with their
instructors, how many course evaluations students have chosen to complete, and how many
assignments they have finished that have required “higher-order learning, includ(ing) more
reading, writing assignments, and reports that (have) challenged (them) to approach the
material in deeper ways.” Grasgreen notes that institutions have reported that, despite the fact
that modern employers in most domains and in most countries have come “to demand
quantitative skills from college graduates, regardless of their chosen career,” not all students in
all subject matters are yet learning “quantifiabilité”: “While seniors in science, technology, math,
and engineering engage most often in quantitative reasoning activities, arts and humanities
majors did so the least,” she reports. And unhappily for the two-year community college, whose
students are often “non-traditional”, often exclusively online, older, or first-generation, “First-generation
online, and adult students were less likely to learn collaboratively, and thus to
engage…”. Thus, not only are these students atypical in the traditional sense of engagement
evaluability, but they may be presenting their institutions with types of engagement that have
until recently been more apparent abroad—such as in Australia, Canada, England, France, New
Zealand, or Sénégal—than they have been here.
The educational model in which students become learners by developing a certain motivation to
design their own programs with the help of academic experts, business mentors, and/or even
government-sourced sponsors may be coming to engage America’s academic community in
ways heretofore unknown.
5 | P a g e
Motivation, sensed and in context
Motivation is “the psychological force that enables action”, as social psychologists Touré-Tillery
and Fishbach (2012) have stated. Generally, basic psychology defines two essential types of
motivation, the intrinsic, generated from inside the curious individual, and the extrinsic,
stimulated in the person by something outside himself. As psychological constructs, both of
these sorts of motivation remain somewhat fuzzy, difficult to measure precisely. While intrinsic
motivation is said to be “caused by the underlying need for a sense of competence and self-determination”,
extrinsic motivation is typically “mediated” by “pay or promotion”, or good grades
in school, as Thakor (1994) summarizes. While it may seem that things extrinsic might be easier
to determine, to measure, than things intrinsic, neither notion is truly fuzz-free.

6. Exemplarily, the California Measure of Mental Motivation comprises “an assessment of the
mindset” of “cognitive engagement and mental motivation toward intellectual activities.”
“Motivated people,” claims the Measure’s creator, Insight Assessment, “are more likely to
engage problems, apply knowledge, and achieve results…”. As Thakor (1994) has stated, an
“operational definition” of intrinsic motivation includes an observation of “(behaviors) performed
in the absence of any apparent external contingency”; things are done because the person feels
like doing them. No “reward” is expected or even hoped for, as it is with external motivation.
Again, as Stipek (2014) has put it, external motivation is easier to measure because, as he
writes, psychologists have long deployed “reinforcement” or “reward strategies” in its execution.
Simply stated, this “mechanistic” practice “feeds” a creature, whose hunger and desire then
encourage him, motivate him, to do more to get more. As Touré-Tillery and Fishbach (2012)
have written, the externally motivated individual is likely “outcome-focused”, interested in a
reward of some kind, while the internally motivated one concentrates on adhering to standards,
as well as the on the joy of achieving accurate results.
Indeed, as Touré-Tillery and Fishbach point out, “tests” of whether an individual has been well
motivated or not often entail measuring “time on task”, how fast that individual might work, and
then how the task may have been completed. It has been observed that speed and performance
both improve as a task is better learned, and so motivation might be a cyclical process, with
success inciting ever more improved motivation.
6 | P a g e
Success, sensed and in context
Success, as Stipek (2014) summarizes it, can mean “winning” in sports or even in politics; it can
be “measured”, Stipek explains, by the length of applause at a performance; it can be clear from
good press reviews or criticism. In the realm of health services, success can mean that patients
have improved, been cured, have survived. In real estate, it is evident if a property has changed
hands successfully.
As Miller (2014) has asserted, since success remains difficult for educators to objectify among
their students, many academic institutions have chosen to measure it simply through student
retention, that quality of persistence described above as the opposite of attrition. But “equating
student success with student retention is both narrow and misleading,” Miller adds, indicating
that it probably accounts for only 20%, at the most, of what can be termed success. Miller goes
on to suggest that, as his own Marymount College has proposed, success comprises at least
five “categorical outcomes”, including retention, educational attainment, academic achievement,
student advancement, and holistic development.
A United States Department of Education “Committee on the Measures of Student Success”
presented in 2011 its own analysis of success, also incomplete, concentrating as it did on
graduation rates to the exclusion of all else. And as the American Association of Colleges and
Universities (AACU) reported in 2007, “Almost everywhere, “college success” is currently
documented through reports on enrollment, persistence, degree completion, and sometimes,
grades. Probed in more detail, states the AACU, “…these metrics for success make it
indisputably clear that college attainment is stratified by income level, and that there are also
significant disparities in attainment between white students and specific groups of racial and
ethnic minorities….”

7. But despite the disparities, or perhaps because of them, educators must recall that, as
Deschênes (2012) has stated, “success is something that must be evaluated, measured, even if
evaluation is considered to be a necessary evil, …if access to programs is to be ensured for all.”
In fact, as Manktelow (2009) advises, “continuous evaluation” should be pursued “to maximize
effectiveness”, to adapt to the changes that he cites as being inherent in the human behavior
that underlies learning.
And so, the fuzzy concepts complainant might ask, how is success to be measured objectively,
particularly if its definition remains subjectively murky? Iteractive Canada’s Michelle Deschênes
(2012) suggests that, in a twenty-first century rich in modern technologies, various active,
interactive, and socially reactive tools be deployed to “integrate” knowledge for “clear and
explicit goals.” It might be noted, though, that although Deschênes calls for clarity and
explicitness, as well as “an attention to detail, to results, (and) to continuous rather than episodic
evaluation” to determine success, she offers no specific examples of how either she or the
Quebec Ministry of Education that she cites might measure it.
7 | P a g e
A (re)new(ed) Learning Paradigm to clip the fuzz?
As Miller (2014) has stated, “when students fail to learn, it is regrettable, but the system doesn’t
change” as it should do; the same old “instructional paradigm” is just pushed harder,
occasionally tweaked, but not really changed, transformed from the inside out. More “experts”
and/or consultants are hired, more “knowledge bases” are conceived, and more effete
awareness is said to inhere in the few. Indeed, even more “specialized”, micro-thinking is often
added, and curricula are “enhanced” by added fuzz. Rather than offering one course in algebra
or calculus that might provide solid foundations in the field and link it to other disciplines in a
practical way, institutions provide a panoply of dizzying, but isolated, options to the prospective
learner. Instructors are encouraged to “develop” themselves professionally in their own fields,
honing their specific expertises among other professors of like kind. Students are expected to
study, to become engorged with new specifics that they will then disgorge upon demand.
In 1995, Barr and Tagg proposed a change to all this that they called The Learning Paradigm, a
pan-institutional proposal which, in sum, held that “no policy, practice, or program should be
instituted or maintained that does not promote student learning”. The Paradigm was in vogue for
a time, but its adherents have, in many instances, all but given up.
A 2008 report by the Middle States Commission on Higher Education, for instance, documents
the suggested implementation of a “Rubric for evaluating institutional student learning
assessment processes” that aims to report the “status” of such Learning Paradigm-generated
notions as: “Clear statements of expected learning outcomes at the institutional, unit, program,
and course levels have been developed and have appropriate interrelationships,” among others.
Once again, it seems that “clear” and “appropriate” cry out to be made precise; Middle States
Commission documents do not provide obvious precision. In Singapore, the National University
has posted a chart on its Webpages showing how the Learning Paradigm differs from the
Teaching or Instructional one, but no apparent examples of the Learning Paradigm are set forth
as being used at that University or elsewhere as we enter the middle of the second decade of
the twenty-first century. “Instruction” comprises unitary thinking, with students being asked to

8. attain simple mastery of rules and structures without much context, while “Learning” is
supposed to be more holistic, uniting subject matters, often using techniques from one area of
interest to clarify concepts in another. And so, as Barr and Tagg pointed out in their 1995
publication on the Learning Paradigm, schools that were beginning in the mid-1990’s to
congratulate themselves on having instituted “critical thinking” curricula as a way to promote
“committed”, “engaged”, “motivated”, “successful” learning-centered student bodies soon
became frustrated, because students and their teachers were not making it obvious either what
such “critical thinking” really comprises or how specifically it operates, particularly in ways
different from what most Instructional Paradigm-trained educators had been used to. Indeed,
“critical thinking” is still all too often taught, using the Instructional Paradigm, as a course or a
set of courses, within a particular curriculum, and in a classroom. As Barr and Tagg have noted,
this is pure absurdity, since thinking critically is a Learning Paradigm practice par excellence,
something that should be instilled, done across the board transdisciplinarily; its processes
should be incorporated into assignments, stimulated in discussions, not set aside as a separate
area of study. Moreover, as Boggs (1999) has observed, surface changes in courses or their
methodology sustain a teaching, or instructional paradigm rather than promoting a learning one.
This, Boggs continues, “confuses a means (instruction) with an end (learning).”
As the American Association of Colleges and Universities suggested in 2007, “a concerted and
collective effort” remains to be made in favor of learning among educators and the society in
which they work, given that the twenty-first century is one of obvious integration of the
academic, the sacred, and the profane. Thus, as the AACU states, it is clear that “Collaborative
action is needed because the impediments to educational excellence are systemic rather than
isolated.”
Solutions to the problems impeding progress must be systemic ones, too, just as Sagna noted
nearly a decade ago in Sénégal. Preferably, these solutions should also comprise something
objective, measurable, accepted as applicable across domains, across disciplines, and around
the world.
But it is still the case that even Tagg (2007), one of the co-creators of the Learning Paradigm,
admits that “most institutions cannot even coherently describe what they are trying to get
students to learn”, much less show whether or not those students have learned. Tagg goes on
to note that, although new jobs in our still-new century often demand “complex communication”
and “expert thinking”, neither of these terms is defined in a non-fuzzy, measurable way. Indeed,
commitment and engagement are cited as desirable traits, proper motivation is expected, and
success in school is supposed to lead to success in the workplace. The problem, Tagg holds,
remains that job-makers and job-givers, just like educators in academic institutions, continue to
think in a top-down way, where knowledge and awareness remain the private province of the
small percentage of people who are on top, and where the task of the larger percentage of us is
to try to penetrate the fuzzy barriers immuring that province.
Tagg suggests that cutting the fuzz can best be done by attending to “better information”, which
he calls concrete, exact, numerical “evidence about educationally relevant activities”. That is,
rather than submitting students to regular multiple-choice or other objective-style quizzes and
tests, teachers in the new learning paradigm should notice whether and how students know
more this week than they did last week, or whether learners in this semester’s courses have
8 | P a g e

9. learned more or in a different way from those who were enrolled last semester, for instance.
Educators must not only become sensitized to such changes but must develop objective means
to measure the shifts.
Indeed, how is “more” or “good” or “better” success to be determined, assessed, evaluated,
measured in the context of the Learning Paradigm? If a school decides to overhaul its policies,
practices, and programs in favor of this supposedly fuzz-free “learning outcomes”-based modus
operandi, how can that school determine whether or not the paradigm is working?
The place to start the assessment of the Paradigm’s own success is, as Pescosolido, et al.,
have stated, in the conventional classroom where particular courses are being taught. From
there, she suggests, assessment is applied to programs and to entire institutions, always
deploying “processes external to instruction,” a practice that should be becoming easier in the
electronic age. Thus, as Pennsylvania’s West Chester University “WCUPA Assessment Brown
Bag Assessment Guide” (2009) states, “an objective assessment is one that needs no
professional judgment to score correctly.” Such an assessment is best determined directly, as
WCUPA asserts, through an analysis of “student products or performances”, a determination of
how well or badly a student can analyze, synthesize, and then apply the knowledge gleaned
from a particular course or program. In a similar manner, the American National Institutes of
Health’s Philogene, et al. (2014) suggest an iterative process of defining for understanding,
identifying, listing, and then re-defining, et cetera.
Sagna would also remind us that education should not be assumed to exist in a vacuum,
particularly in a twenty-first century in which learning happens at home, in the workplace, on the
street, and online, as well as in the classroom, at any time of day or night. As Boggs (1999) has
written, the Learning Paradigm holds that learning is an exciting, unrestricted, “unbound”
process; Sagna notes that it is also holistic and continuous, infusing thought processes,
attitudes, and behaviors in constant change.
But it remains difficult to determine objectively the feasibility of applying the Learning Paradigm
to measure commitment, engagement, motivation, and success, especially since these terms
are unexceptionally fuzzy. A European Union 2008 report on “learning to learn” establishes
standards for testable “computer literacy”, “reading comprehension”, and “knowledge of the
natural and social world”, among other indicators of educational success; the standards are
flexible, and European institutions that subscribe to them are expected to share student work
among participant institutions from Finland to Portugal to France to Greece, and elsewhere. At
the University of Helsinki, for example, students arrive after having been tested more than once
a year in mathematical and other reasoning skills, in their ability to communicate in speech and
writing, and in their understanding of the significance of various world events, starting from age
11 and continuing through university. In a Barr and Tagg-like Paradigmatic way, educators
determine how these students are learning, as well as what they are learning, how they are
changing from one semester to the next, how their commitment and engagement are or are not
exhibited in their measured motivation. The European Union report cites a development of
“critical curiosity” and “strategic awareness” as being measurable through rubrics devised by
educators at more than a dozen institutions throughout the Union. Indeed, it might do American
educators well to see how these rubrics can be applied in our own institutions for learning, while
at the same time heeding Sagna’s call to ensure that our schooling, if it is to develop truly
9 | P a g e

10. educated citizens successfully, is integrated into community, society, politics, and the greater
world.
10 | P a g e
REFERENCES
American Association of Colleges and Universities. (2007). College learning for the new global
century. Retrieved http://www.aacu.org/sites/default/files/files/LEAP/GlobalCentury_final.pdf
Barr, R. and Tagg, J. (1995). The Learning Paradigm. Retrieved
http://pacweb.alamo.edu/FacultyDev/pdf/Pats_files/Linda%20Suskie/BibFiles.pdf
Boggs, G. (1999). What the learning paradigm means for faculty. AAHE Journal, pp. 3-5.
Retrieved http://www.vet.utk.edu/enhancement/pdf/feb11-2.pdf
Brault-Labbé (2007). Erudit. Retrieved
http://www.erudit.org/revue/rse/2008/v34/n3/029516ar.html
California Measure of Mental Motivation. Critical thinking attributes. Insight Assessment.
Retrieved http://www.insightassessment.com/Products/Products-Summary/Critical-Thinking-
Attributes-Tests/California-Measure-of-Mental-Motivation-Level-III
Change magazine. (2011). Student engagement abstract. Retrieved
http://www.changemag.org/Archives/Back%20Issues/2011/January-February%202011/student-engagement-
abstract.html
Committee on Measures of Student Success. (2011). Final report. Retrieved
http://www2.ed.gov/about/bdscomm/list/cmss-committee-report-final.pdf
Dechênes, M. (2012). Evaluation, le web social. Iteractive. Quebec Ministry of Education.
Retrieved http://iteractive.ca/evaluationwebsocial/evaluation.php
Fletcher, A. (2011). Student engagement. Sound Out. Common Action Consulting, Olympia,
WA. Retrieved http://www.soundout.org/student-engagement-AF.pdf
Grasgreen, A. (2013). Measure student engagement and learning outcomes. Inside Higher Ed.
https://www.insidehighered.com/news/2013/11/14/nsse-2013-measure-student-engagement-and-
learning-outcomes
Hackman, J. and Dysinger, W. (1970). Commitment to college. Harvard University. Retrieved
http://groupbrain.wjh.harvard.edu/jrh/pub/JRH1970_3.pdf
Hanson, E. (2012). Educational Leadership. ASCD Journal. Pp. 141-145. Retrieved
http://www.ascd.org/ASCD/pdf/journals/ed_lead/el_195512_hanson.pdf
Hanson, J. (1995). Integrating learning styles and multiple intelligences. ASCD Journal.
Association for Supervision and Curriculum Development. Retrieved http://www.ascd.org

11. Hardy, C. and Bryson, C. (2012). Student engagement: Paradigm shift or political expediency.
Higher Education Academy, Brighton, UK. Retrieved
http://www.adm.heacademy.ac.uk/resources/features/student-engagement-paradigm-change-or-
11 | P a g e
political-expediency/
Hoskins, B. and Fredriksson, U. (2008). Learning to learn: What is it and can it be measured?
European Commission. Retrieved
http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/979/1/learning%20to%20lea
rn%20what%20is%20it%20and%20can%20it%20be%20measured%20final.pdf
Jay, G. (2012). The engaged humanities. Journal of Community Engagement and Scholarship,
vol. 3, no. 2, University of Alabama. Retrieved http://jces.ua.edu/the-engaged-humanities-principles-
and-practices-for-public-scholarship-and-teaching/
Jenzabar, (2013). Achieving meaningful student success. White Paper. Retrieved
http://www.jenzabar.com/sites/default/files/resource-downloads/
Jenzabar_Retention_WhitePaper_web.pdf
Koshar, J. (2014). Nursing research and evidence-based practice. Sonoma University.
Retrieved http://www.sonoma.edu/users/k/koshar/n300/week03_PRviews.html
Manktelow, J. (2009). Team building tool kit. MindTools. Retrieved
http://www.utexas.edu/facilities/about/qapi/documents/TeamBuildingToolkit.pdf
Michit, R. (2008). Introduction: Une vieille question trop vite enterrée. Science humaine, science
exacte, les normes de la pensée sociale. Mémoire Online, Université de Grenoble. Retrieved
http://www.memoireonline.com/07/08/1429/m_science-humaine-science-exacte-normes-pensee-
sociale1.html
Miller, B. (2014). Five outcomes to student success. Ellucian blog. Retrieved
http://www.ellucian.com/Blog/Five-outcomes--to-student-success/
Miller, H. Paradigm shift. http://www.hermanmiller.com/research/research-summaries/
paradigm-shift-how-higher-education-is-improving-learning.html
National University of Singapore. (2008). Learning to teach, teaching to learn: A handbook for
NUS teachers. National University of Singapore. Retrieved
http://www.cdtl.nus.edu.sg/handbook/learn/paradigm.htm
Northern Territory Government. (2014). Individual commitment to learning. NT, Australia.
Retrieved http://www.education.nt.gov.au/teachers-educators/professional-learning/
framework/committment
Parsons, J. and Taylor, L. (2011). Student engagement: What do we know and what should we
do? University Partners, University of Alberta, Canada. Retrieved
https://education.alberta.ca/media/6459431/student_engagement_literature_review_2011.pdf

12. Pescosolido, B. (ed.) (1999). The Social Worlds of Higher Education, vol. 2. Thousand Oaks,
California: Pine Forge Press.
Philogene, G. (ed.) (2014). Objective measurement of subjective phenomena. National
Institutes of Health New England. Retrieved
http://www.esourceresearch.org/eSourceBook/ObjectiveMeasurementofSubjectivePhenomena/
1LearningObjectives/tabid/693/Default.aspx
12 | P a g e
Sagna, O. (2005). Etat des lieux. OSIRIS. Retrieved
http://www.researchictafrica.net/countries/senegal/OSIRIS_2005.pdf
Stipek, J. (2014). Defining achievement motivation. Education.com. Retrieved
http://www.education.com/reference/article/defining-achievement-motivation/
Tagg, J. (2007). Learning communities. Student Services, San Diego City College.
https://www.sdcity.edu/Portals/0/CollegeServices/StudentServices/LearningCommunities/Pedag
ogicalInsightProcess/ChangingMinds.pdf
Te Kete Ipurangi. (2014). Commitment to learning for all. New Zealand Ministry of Education.
Retrieved http://instep.net.nz/Appendix-II-Professional-learning-communities/What-is-a-
PLC/Commitment-to-learning-for-all
Thakor, M. (1994). Innate: Development of a new intrinsic motivation measure. Asia Pacific
Advances in Consumer Research Volume 1, 1994. Pp 116-121. Retrieved
http://www.acrwebsite.org/search/view-conference-proceedings.aspx?Id=11190
Touré-Tillery, M. and Fishbach, A. (2013). How to measure motivation: A guide for the social
psychologist. University of Chicago. Retrieved
http://faculty.chicagobooth.edu/ayelet.fishbach/research/SPCOTilleryFishbach.pdf
WCUPA. (2009). Assessment Brown Bag. Retrieved
https://www.wcupa.edu/tlac/documents/More%20on%20Measures--Definitions.pdf
Zadeh, L. (1997). Toward a theory of fuzzy information granulation. Fuzzy Sets and Systems,
vol. 90. Elsevier, pp.111-127. Retrieved http://sci2s.ugr.es/docencia/doctoSCTID/Zadeh-
1997.pdf