In Caddo parish, there are less than ten thousand educators serving over forty thousand students. (Goree, 2015) This ratio may seem high by proportion, but readers are reminded that the number includes teachers, their assistants, administrators, cafeteria and janitorial service, bus drivers, and numerous other support-roles provided by occupations which don't come to mind when thinking of education. In fact, according to one source, actual teachers only occupy about 2500, or a little over a quarter of the whole pie. This brings the literal teacher/student ratio to about 16:1 average. If the widely criticized achievement gap still exists after a certain period under these conditions, it becomes necessary to look beyond reducing class sizes for solutions. In so doing, educators should look to successful systems for new strategies, because differentiation is always occurring, but evolution requires adaption and replication of those successful strategies in order to function. However, educators should also be cautious of their own enthusiasm for new concepts and approaches, so that the critical focus remains upon student achievement and is not lost in theory and abstraction, while keeping grounded firmly in the practical.
One strategy which lends itself to this discussion comes from Finland. According to AsiaSociety.org, Finland “abolished standardized testing.” (AsiaSociety, 2010) How on earth do they keep track of which ones are the slow students and smart students? The answer (they don't, really) is indicative one of the prevailing flaws in the premise of the information age. This article suggests that the quality of Finland's educators is an outcome of the selection process, and that in order to obtain entry into the field, candidates “must graduate at the top of their class.” (Ibid) Instead of worrying about predicting which students will and won't graduate, the Fins managed to deliver the most competitive international achievement results just by counting who actually did and did not graduate. Until that point, educators enjoy a “trust based system,” which is literally and philosophically the opposite of America's Common Core mandate. The article reports that Finland “has the top-ranked school system in the world,” as indicated by a “high graduation rate,” equal education access, and high marks on international testing. (Ibid)
Some reasons why no one should find this outcome shocking are as follows: First, Testing is not Teaching. Therefor, reducing the time spent preparing and taking tests allows a budget-safe way to increase actual lecture and study time. Second, Testing requires analysis. In order to facilitate this data-centric approach to teaching, effort is drawn away from the actual process of accomplishing the task itself in order to aggregate and analyze immense amounts of data in the abstract. The very process has resulted in converting our students into research projects which glean more information for researchers than they absorb from educators, while converting our educators into consumers of high-end, proprietary, budget-killing tech with rapid obsolescence rates and diverse hardware requirements. Third, the testing itself becomes the basis of broad (and flawed) assessments of student's latent capacities which are then projected onto the identities of the students themselves, often with harmful and counterproductive effects.
Looking outward may also help us to put our own outcomes into perspective. In Canada for instance, “64% of adults aged 25 to 64 had post-secondary qualifications in 2011.” (Statistics Canada, 2015). Such numbers are not disimilar to rates in the US. But Canada has made great strides in leveling the gender gap: “Young women aged 25 to 34 held a larger share of university degrees (59.1%), compared with their share of 47.3% among older age groups of 55 to 64.” (Ibid) Perhaps this example serves as a cautionary tale. Canada took a 4% gender gap and created a 10% gender gap. The critical philosophical question reduces to a set of dueling altruisms: Has Canada succeeded in eliminating a nearly 8% achievement disparity in women's favor, or merely created a 14% gap at the expense of males? We will return to Canada in a moment, but first it is necessary to focus this idea of critical skepticism.
A report on tutoring strategies in Latin America released by the Carnegie Mellon (Carnegie Mellon) university challenges the popular conceptions about technology in education (technology, being the inherent origin of all the new data-mining and metric-analysis persuasions which resulted in first-world obsession with standardized testing in the first place) by shining light on some of the failed experiences to implement new tech among educators in Latin America. Broadly, the authors of this report highlight the distinction between emphasis on “technological innovation” versus “transforming teachers and practices.” (p. 1) In short form, the best efforts of well-intentioned software developers fell short because they didn't take into account the conditions on the ground.
The assumption seems to have been that the mere presence of technology would be sufficient to make up for the shortcomings of teachers. More specifically, the article refers to “hundreds of studies of failed technological interventions...” which “failed to adapt to the social and technological systems...” (p. 11) In the specific case of educational systems enhanced by technology, the teacher, classroom, school, district authorities, and parents are a part of the social system.” It is not difficult to understand, then, why “performance in national and international tests (e. g. PISA, TIMMS) in the Latin American region has not increased as expected. (Ibid) Among other advantages, the data-centric approach offers what are known as “indicators of effectiveness,” which, in theory, enable educators to evaluate the different methods they employ by studying the rates of failure and success at specific tasks or by specific students. But evaluation works both ways, the authors suggest. Those who place a high premium on such indicators should be willing to acknowledge that when the software (or tests) fail or is rejected by teachers, those are “indicators of ineffectiveness.” (Ibid)Educators should be reminded that software companies are thus incentivized to please teachers, and should endeavor to promote a similar relationship with parents and polity as well, without succumbing to the culture of bribery and aggressive solicitation associated with drug and insurance companies.
Moreover, educators should also remember that a healthy skepticism is just a moderating approach, and that there are still positive outcomes to be had. The Carnegie Mellon report describes at least one system which yielded “a high percentage (67%) of experimental students [who] increased their motivation toward learning math.” (p. 11) While such meaningful responses remain the golden grail in America, sober reflection reminds us that conditions in Latin America may be widely different from those here in Caddo Parish. For instance, technology itself has a highly observable impact when it is new, but can be less effective over time, and with students who are not new to it. For this reason, educators should focus on utilizing the technology they have available, and integrating the students' own experiences into the strategy, rather than endorsing district and statewide implementation of new platforms which are extremely costly and increase the complexity of the over all process in disproportion to expectations, let alone actual outcomes.
Departing from the test-and-tech strategy does not necessarily make things easier, however. Scholarly efforts to reduce the achievement gaps are wide and diverse, but many disciplines have centered on motivation as a key component in distinguishing the strong performers from the weak. Explanations on why students disengage and how to reengage them are equally divergent. Edward Hootstein (1996) examined the challenge of “motivating at-risk students” (which is quite different from motivating gifted students), and developed the RISE model. In this approach, they key psychological factors to consider are “relevance, interest, satisfaction, and expectation.” (Ibid) In summary, educators must illustrate how the material is connected to the student's life in a way that engages the student. Among many other tips, the author emphasizes that teachers must “promote the student's sense of control over learning activities,” and “provide rewards that have information value.” (Ibid) Another unique strategy is to trick the disengaged students into reengaging: “create a discrepancy by providing incongruous, conflictual, and paradoxical information.”
Concerning motivation, other scholars have offered less mischievous, but no less cerebral, suggestions. Carl Rhine (1998) synthesizes three broad headings, under which most focuses for improvement may be filed. One concerns the characteristics of the learner, which precedes the (partially-debunked and progressively discouraged) testing and analysis approach. Another seeks to alter instructional methodology, perhaps by implementing new technology or teaching strategies. The last focuses on the characteristics of the content itself. (Is it interesting, relevant, etc...) It is easy to extrapolate the different ways in which these might be related to motivation. In the first, one might ask whether the student best responds to material in print, or in spoken explanation, or in a hands-on setting. The second might ask about the teacher's use of a given learning aid over a textbook. The third might consider tailoring the curriculum to the local community's cultural and social conventions.
A case study in the Journal of Educational Research (2012) examined motivation as it relates to three different hypothetical vectors within the student: self-concept, self-efficacy, and self-esteem. The first refers to who a student believes they are. This can dictate whether students lean more naturally toward books, balls, or the ballot, and can help educators trying to target strategies toward struggling students by knowing something personal about how they see themselves. The second refers to how students evaluate their own abilities. The author's of this study make an interesting note about the transition from over-confident but poorly-reasoned self evaluations made by small children to under-confident but more analytically accurate self-evaluations made by older students. The third is basically ego, or an appraisal of how the rest of the world sees the self. Each of these perspectives must be useful in trying to find ways to build motivation in students.
Coming back to Canada, another detail may help us to better understand the challenges of eliminating these education and achievement gaps. While a plurality of college graduates within a certain age bracket are female, the article (referenced above) mentioned that “almost 8 in 10 Registered Apprenticeship Certificates were held by men.” (Statistics Canada) From the dispassionate perspective of an economist, neither sector of entrepreneurial is expendable. Both career trajectories may potentially yield incomprehensible fortunes or mundane, third-world slave wages. Mostly, society needs bankers just as much as builders, and so the time comes for us to begin assertively reevaluating the social segregation of academia and vocation. By prefabricating an arbitrary, class-centered, psychological barrier between these two groups of industry, we have all catered to the suggestion that one is favorable or preferable to the other. As a result, students tend to associate each of these directions with preexisting, received assumptions about character and validity. Some students with higher socioeconomic status might perceive welding as common or demeaning, while other students might perceive advanced degrees in physics or law as elitist and patrician. Conversely, female students might reject opportunities in science and engineering for liberal arts degrees, while men might forsake a college education altogether in favor of a vocation. The inevitable result of this, regardless of its causality, is structurally perpetuated stratification and occupational bias which reinforces existing racial, gender, and socioeconomic divisions.
These are mindsets that must be broken during the most formative periods of a child's life, which is often when valences for their creation are most intensely expressed. One way to do this is to reunite the humanities with the vocations during the primary education period. A generation of children who learn conventional trade-skills alongside the Three R's in elementary, middle, and high school should be more likely to find economic opportunities afterward. Additionally, colleges could consolidate these gains and others but replicating this mentality. Consider the case of Louisiana State University of Shreveport and the Louisiana Technical College, for example. The two campuses are 12 miles apart. The one offers four-year degree programs for undergraduates in business, medicine, history, and education, among others. (LSUS.edu) The other offers industrial certifications in for AC/Hvac technicians, electricians, and mechanics. (NWLTC) Students who attend these two campuses are scattered across the two cities (Shreveport and Bossier) and the surrounding areas, and some commute from further.
From a design perspective, this is an illogical distribution. There are incredibly useful skills and experiences to be obtained at either institution, but students attending the one are almost guaranteed never to be exposed to the other. A historian has just as much to value in learning how to wire houses and electronics as a welder has in learning about how man and society evolved in the universe. Instead, we have dissonance between these generalities, a set of opposing armies of blue and white collar citizens constantly being driven toward the opposite ends of multiple spectra, such as political, ethnic, and religious. Combining the two facilities at the very core structural level would force the two groups under the same socio-conceptual umbrella. But from a purely material point of view, drawing an imaginary line between the two campuses and distributing the classes among the two based on the average distances of attending students in favor of the local majority in either case could potentially save most students thousands of dollars in transportation. A more broad economic advantage would follow this cultural integration as a consequence of expanded network exposure between the professional and vocational sectors.
Similarly, at the parish level of secondary education, this principle is simulated in the districting requirements which mandate attendance relative to residence. The inherent goal is to prohibit racial and socioeconomic stratification by preventing the distributive mechanism of natural selection, in which one school with a reputation for success draws a flood of attendees while flight patterns cripple the neighborhoods where schools struggle. The distinction between these areas is learned and internalized by students as a component of identity, which then guides later perceptions about ability and opportunity. It is impossible to prevent socioeconomic differentiation from neighborhood to neighborhood, but it is possible and even practical to try to mitigate those effects at the regulatory level.
We hammer away at these divides with tests and technologies that do as much to underscore our primary differences as to soften them, but we haven't gone far enough toward breaking down the cultural stereotypes inherent in our own foundation which perpetuate the unfavorable standards. Get rid of the tests; give the classes back to the teachers; try to reintegrate class perception about industry, and don't hang the students' future on passing innovations.
Works Cited
Image Source: https://www.exeter.edu/documents/ss_harkness.jpg
----- “Academic Programs,” Nwltc.edu, http://www.nwltc.edu/air-conditioning-refrigeration/ (accessed 13 July, 2016).
---- “A Cognitive Tutoring Strategy for Math Teaching and Learning in Latin America,” Carnegie Mellon University, http://www.contrib.andrew.cmu.edu/~jpi/papers/teacher%20training%20paper%20pdf (accessed 13 July, 2016).
----- “Areas of Study,” Lsus.edu, http://www.lsus.edu/areas-of-study (accessed 13 July, 2016).
Bong, Mimi, Cho, Catherine, Ahn, Hyun Seon, and Kim, Hye Jin. “Comparison of Self-Beliefs for Predicting Student Motivation and Achievement,” Journal of Educational Research, Vol. 105, p. 336-352, 2012.
----- “Education in Canada: Attainment, Field of Study, and Location of Study,” Statistics Canada, https://www12.statcan.gc.ca/nhs-enm/2011/as-sa/99-012-x/99-012-x2011001-eng.cfm (accessed 13 July, 2016).
Goree, Lamar., “2012-2016 Mini FACTS,” Caddo Parish Public Schools, Communications and Marketing Department, November, 2015 http://www.caddoschools.org/files/2015-2016MiniFACTS.pdf (accessed 13 July, 2016).
Hootstein, Edward., “Motivating at-risk students,” Clearing House,Vol 70, Issue 2, p. 97.
Rhine, Carl., “Motivating Students is a Percentage Game,” Phi Delta Kappan, Vol. 79, Issue 2, p. 620.
----- “What Accounts for Finland's High Student Achievement Rate?” AsiaSociety.org 27 April, 2010 http://asiasociety.org/global-cities-education-network/what-accounts-finlands-high-student-achievement-rate (accessed 13 July, 2016).