Institutional Resistance to Innovations in Education

Resistance to Improving Learning and How to Manage Change

Innovation is costly. To not innovate is to perish slowly. The ever-increasing pervasiveness of information is changing how students learn, as exemplified by continuing sophistication of online delivery methods and emerging universities in meta-verses, such as Duke University’s School of Nursing in Second Life. High-fidelity graphics, 3D modeling, and digitally controlled simulations continue to provide new ways for students to blend content with near-real world experiences that enhance learning. Adopting new learning methodologies often requires changing roles, creating new learning activities, and engineering innovative ways to accomplish learning assessments. All learning establishments are engaged in conversations about which pedagogies are best, which ones are affordable, and how to implement changes that improve student performance while resisting learning technologies that are costly distractions. Most universities are expanding the spectrum of learning mediums, offering a wider array of education and training opportunities to fit the various lifestyles of an increasingly more diverse and globalized customer base.

Some institutional business practices may reinforce resistance to education and training innovations. Technological determinism suggests that educators should accept technological change without requiring significant performance gains. Rational thought suggests that successful organizational innovations will result in better efficiency, effectiveness, or satisfaction. But, what costs are acceptable and defendable to traditional learning organizations? Improving efficiencies in training and education includes reducing the time it takes for students to learn specific content or skills. Increased effectiveness includes enhancing the quantity and depth of learning that occurs during the same time periods as previous methods. Additionally, increasing satisfaction includes increasing student and faculty satisfaction with the learning experience. Continuous process improvement and technological determinism philosophies in education challenge traditional pedagogies, term lengths, accounting models, and learning expectations.

Education and training institutions support resistance when institutional accounting and incentives fund instructors and staff based upon student flow and course length, or are tied to specific teaching practices. At many learning institutions, instructor positions are calculated based upon the number of students entering training and the length of the course. If the course length were to diminish, so would the number of instructor positions. If instructors were to innovate and reduce the length of a course, then they would essentially be working themselves or their peers out of a job.

Additional resistance emerges when these same learning organizations measure stakeholder satisfaction rates. The current teaching methods may have generated years of satisfied supervisors who then employ the trained and educated graduates. In many instances, a 99% rate of satisfaction may not have changed in over 20 years suggesting that 20-year-old methodologies and pedagogy are still the best. In these instances, institutional measures may reinforce resistance to educational innovations.

Many examples of creating organizational cultures that embrace innovation, such as Toyota, provide long lists of best practices that may improve education organizations’ chances of embracing productive innovations and engineering a more adaptive culture. One best practice involves embracing aggressive continuous process improvement (CPI). A second is the re-training, instead of dismissing, of educators that are no longer needed in their original roles. A third is to incorporate adjustable activity-based costing (ABC) to properly account for the activity adjustments that are required to innovate. Faculty will not innovate if they do not have support to measure, introduce, and sustain continuous improvements. Neither will they innovate if doing so reduces job security or benefits. Finally, innovation will be stifled by institutional accounting practices that do not properly initiate, appreciate, and fund innovation.

Continuous Process Improvement in Education

Continuous Process Improvement (CPI) is a term that has emerged from the revolutionary works by W. Edwards Deming on quality. The earliest applications of CPI were made in Japan, termed kaizan. The focus of kaizan has been mostly in manufacturing and logistics corporations. However, the principles may apply in education and training institutions as well. CPI is intended to produce a culture that expects and rewards innovation and precision. Education and training institutions have numerous processes where CPI could be applied. Creating a culture where CPI will produce results may require attention to a few of Deming’s key points. Deming’s first of fourteen points is to “create constancy of purpose for the improvement of products and services” (Walton, 1986, p. 55). His fifth of fourteen points is “improve constantly and forever the system of production and service” (Walton, 1986, p. 66). The technical school and university ought to pursue continuous product and service improvements just as other industries. In concert with Deming, educators ought to continuously improve learning, which should translate to the reduction of time required to learn a set amount of material or an improvement in the depth of understanding that takes place in the same amount of time, or an improvement in student and employer (customer) satisfaction. Specific term lengths, inconsistent content delivery, and inconsistent business practices that dilute the purpose of improvement may be working against CPI in formal training and education institutions. Even so, many course development methodologies incorporate steps for feedback and revision, and these steps may be better leveraged to generate a culture of continuous process improvement.

Educators ought to stay true to foundational instructional systems design methods while vigorously emphasizing the feedback and innovative improvement steps. Most educators are well aware of Instructional Systems Design (ISD) methods (Dick, Carey, & Carey, 2001). Additionally, many educators have worked extremely hard and take great pride in the courses they have designed. Professors that have worked hard to create a course that appears to work well enough with current students are not usually motivated to re-design their course to incorporate emerging technologies. Unfortunately, longitudinal effects of not improving education and training may include the eventual lower quality of knowledge and skills of students in relation to those of more adaptable programs. Educators should not wait for dissatisfaction indicators before blending in new technologies.

Another component of CPI is precise measurement. Deming is quite well published in his use of statistics to improve processes and services. Educators ought to develop keener assessments that provide better ways of measuring process performance and then implement specific, proactive interventions. Current assessments of learning are most often aligned with term lengths. Courses are stacked and aligned according to traditional pedagogical practices that limit each course to a specified number of learning objectives, and often a lengthy learning period. Student performance measures are usually taken throughout the term but are only fully acknowledged at mid-term and at term completion. Improved learning means shorter terms or deeper understandings. The number of learning objectives, types of assessment, and course alignments are all determined by the experiences of faculty and their perspectives of student learning. Professors decide how much content to deliver, how to deliver it, how to assess learning, and when to assess learning. Professors and academic departments also decide upon the grades to give, how to curve performance feedback to account for variations between sections, and how to adjust performance feedback to account for variations in delivery methods. However, student grades are most often viewed as the measure of student performance and not a measure of course performance.

Current assessments in training and education may not provide precise enough measures to determine the quality of learning taking place as intended by CPI. Philosophically, education and training institutions have to consider that student performance is a function of course design, course delivery, and instructor leadership. However, my experience is that many faculty deflect poor student performance back onto the students. Often I have advised students who struggle in training and education courses because they have encountered a learning gap, a learning style conflict, or remain unmotivated and uninterested in the content. Often faculty responds to these challenges by criticizing student intelligence, ability to adapt, and/or effort levels.

A learning gap occurs when the content of a course begins well beyond the student’s current knowledge/ability level. The gap exists because the course was designed for students who had a stronger experience in both content and context. A common place this can be found is in the teaching of calculus. Many students, even ones that received A’s in algebra and trigonometry, struggle with calculus. Visual learners especially, may struggle conceptualizing the purpose for the complex calculus methods. In a set term length, calculus classes must take a group of students and move them through content at a rapid pace. Those students who had taken previous calculus courses may do well, while the students who have not had a successful calculus background continue to struggle with the “why” and “how” of calculus functions. Yet, many calculus professors do not bother establishing pedagogy to bridge the learning gaps of their students. They often blame the students for not adapting to the intense practice modules necessary for developing proficiency, and for not being motivated to excel in the course.

Integrating leadership is Deming’s seventh of fourteen points (Walton, 1986, p. 70). The professor ought to be the leader in the learning environment. Good leaders are able to increase the motivation and performance of their followers by sharing a common vision, establishing common goals, and providing the resources and knowledge necessary to achieve excellence. For Deming, effective leadership adapted to the situation, accepted responsibility for failures, innovated ways to prevent future errors, and motivated others to adapt their behaviors to achieve higher levels of success (Deming, p. 71-2). We can improve learning by taking responsibility for both student and course performance and seek ways to bridge learning gaps, help students adapt to new disciplines, and motivate students towards common purpose.

Current methods of assessing student learning are rarely accurate enough to inform educators of how to improve course design and course delivery. For example, many instructors are cognizant of “high-missed” questions and remove them from course materials, thus simply eliminating the measure instead of improving the instruction. Most instructors that I know adjust their course content between each term based upon their gut feeling or preferences, not data. In most cases in which I am familiar, data does not inform significant changes to course design or delivery, and continuous process improvement is not a faculty concern because student performance is a reflection of the student, not the course. By failing to improve education and training environments, we disadvantage both our students and our future workforce, as their skills and abilities will continue to fall behind those of students from education and training systems that are more in tune with continuous process improvement.

Improve Training and Retraining

Deming’s thirteenth point is to “institute a vigorous program of education and retraining” (Walton, 1986, p. 84). The focus of training is to reduce the errors or the activities that do not bring forth the greatest gains in quality of product or services. For educators, it means eliminating activities and methods that do not bring forth the highest level of learning. The concept may be applied to both students and faculty. The concept challenges learning organizations to develop rigorous training programs to ensure new instructors and students employ the best practices. Constructivist theorists may resist these notions and claim that student learning styles are unique and therefore one right way to teach and learn is irrational. However, identifying the educating practices that result in the highest quality learning can be made inclusive of learning styles and grounded in the scholarly discussions of emerging methodologies.

Re-training implies an understanding that continuously improving learning will reduce the amount of time necessary to reach intended learning outcomes, thus reducing some of the tasks currently accomplished by faculty. Deming realized that losing skilled workers is extremely expensive. It is cheaper and better for the institution to re-train current workers versus recruit new ones. Toyota often boasts of the high success of its re-training policies while its competitors often fired permanent workers who were replaced with new technologies and new processes. The fear of unemployment, especially in today’s economy, is a key factor as to why many employees will not innovate or take risks without high-levels of support and institutional incentives to do so.

Applying Deming principles to education yields interesting discourse about current continuous process improvement and instructional design, learning assessments, and precise measurement of course quality, and increasing the amount and quality of faculty training and re-training. However, these ideas will not be enough to generate better learning environments alone. They must be accompanied with more flexible business and accounting practices. Activity-Based Costing may play a key role in combating resistance to innovation in education and training environments.

Activity-Based Costing

Activity-Based Costing (ABC) is an accounting methodology that more accurately costs the activities and overhead necessary to provide products and services. Institutions involved in ABC tend to be more flexible and more correctly allocate resources (Ness, 1995). Applying Time-Driven Activity Based Costing (TDABC) may be critical to ensuring our learning institutions are correctly structured and incentivized to innovate (Kaplan, 2007). Institutions are indirectly asking how much it costs per time unit to integrate emerging technologies in a cohesive and meaningful way and how much time is required to perform the work needed to provide high quality learning (Kaplan, 2007).

Faculty members spend a lot of time preparing for their classes, grading, conducting research, publishing works, and participating administratively. Many faculty members that I converse with state that they do not have much time to research and develop alternative delivery methods, nor are they fairly compensated for doing so. Deming’s earlier quality discussions suggest that perhaps we do not want instructors to innovate. Outsourcing may become a more sought after solution.

Outsourcing the design and development of increasingly more effective instructional systems may become more apparent to institutions that implement ABC, just as Chrysler saved hundreds of millions of dollars when it outsourced the manufacturing of parts after it implemented ABC and realized the true costs of manufacturing the parts internally. ABC applied to learning institutions may improve efficiency, effectiveness, and adaptability of education and training.

Institutions need to reach further into accounting practices to gain an appreciation for the activities that engage faculty. Continuous process improvement and innovation require additional investments and alter the activities that faculty and staff have traditionally accomplished. Implementing more accurate accounting methods that flex with changing activities and incentivize innovation, investing in more rigorous training and re-training of faculty and staff, and energizing the feedback and revision steps of the instructional design process are likely to result in a reduction of the resistance to integrating emerging technologies. The results are likely improved quality of education and training in ways that will not be measured on satisfaction surveys.