By Margaret Long, Adrienne Cottrell-Yongye, and Tyler Huynh
A challenge across K–16 education is how to enhance student learning by deepening students’ understanding. Backward design, part of Understanding by Design (UbD), is an evidence-based method first used in K–12 education as an alternative to traditional curriculum design (Wiggins & McTighe, 2005). In traditional curriculum design, the textbook or an educator’s ideas for the course serve as the guide that frames the design of instructional activities, followed by the creation of assessments (Wiggins & McTighe, 2005). Backward design leads to a curriculum that uses lesson standards or objectives to guide the creation of assessments and instructional activities (Wiggins & McTighe, 2005). Backward design’s effectiveness in enhancing students’ learning has been demonstrated in elementary (Kurson, 2014; Mesa & Sorensen, 2016), middle (Hendrickson, 2006), and high school science curricula (Jorgensen, 1994; Wang & Allen, 2003). Backward design has been effective for supporting and enhancing the learning of both students who excel and students who struggle (Childre et al., 2009). Even in higher education, backward design is viewed as a useful guide in transitioning curriculum from teaching-centered to learning-centered (Davidovitch, 2013; Withers, 2016).
Although backward curriculum design has been implemented in the redesign of higher education STEM curricula (Daugherty, 2006; Scott, 2015; Shah et al., 2018), studies evaluating its effectiveness in higher education are limited. Kelting-Gibson (2005) used backward design to redesign a preservice education student course on curriculum development and compared the performance of students taking the backward-designed course to control for students taking the same course taught in the traditional, prebackward design format. The results showed that preservice students in the backward design course outperformed students in the control group in all criteria measured (Kelting-Gibson, 2005). Minbiole (2016) redesigned a nonmajors biology course using backward design and observed an increase in final exam grades in the redesigned course compared to the previously taught traditional curriculum design. Minbiole (2016) also found a significant increase in the percent of students earning final grades of A and B in the redesigned course compared to the previous course. Information regarding backward design is lacking at the two-year, technical college level. The purpose of this study was to implement the backward design model to redesign a nonmajors biology course at a two-year technical college. The aim was to measure its effectiveness in enhancing students’ learning and success in the course, as measured and defined by course retention and passing with a C grade or better. The reporting of this study is twofold: It includes a description of how backward design was used to redesign a nonmajors Biology I course at a technical college, and the results of implementing the course redesign.
Traditional, linear course planning may lead to a lack of understanding of learning outcomes by students and misalignment of learning outcomes with assessments and course materials (Fink, 2007; Minbiole, 2016). There are three steps in the backward design model: (1) learning goals are first determined based on the big ideas in the course, which leads to (2) the development of essential questions, and (3) curriculum design that is rooted in the essential questions (Wiggins & McTighe, 2005). The learning goals dictate the creation of appropriate formative and summative assessments that monitor students’ understanding and correct their misconceptions (Wiggins & McTighe, 2005). Lastly, learning experiences and instruction are constructed based on the learning goals and assessments (Wiggins & McTighe, 2005). Wiggins and McTighe (2005) argue that using backward design leads to greater understanding because this curriculum model focuses more on student output and aligns instructional activities with assessments and learning goals.
The UbD protocol for backward design provides a structure to plan rigorous curriculum and teach for understanding (Wiggins & McTighe, 2005). UbD and backward design of curricula have led to significant improvements for K–12 students (Brown, 2004). The backward design model was first introduced in the K–12 system (Wiggins & McTighe, 1998), and it has recently been used in higher education to redesign undergraduate science courses (Minbiole, 2016; Momsen et al., 2010; Scott, 2015).
Using backward design allows instructors to share course objectives clearly with students, improve course coherence, and develop valid assessments (Wiggins & McTighe, 2005). UbD, thoughtful curriculum planning, and continuous curriculum improvement enhance student learning experience irrespective of background (Brown, 2004). Traditionally disadvantaged and/or underserved student populations such as minority students, nontraditional-aged students, and first-generation college students typically show achievement gaps in college science courses (Minbiole, 2016; Packard & Babineau, 2009; Wilson & Kittleson, 2013). Students from these populations show enhanced understanding and improved academic performance when curriculum and assessments undergo continuous development (Burk, 2000; Kamler & Comber, 2005; Minbiole, 2016). There is little research on the effects of backward design on curriculum and curriculum development at the technical college level and the benefits to traditionally disadvantaged and underserved groups of technical college biology students.
Biology I at Gwinnett Technical College (GTC) is a nonmajors, introductory biology course, and, like other nonmajors biology courses at two-year colleges, plays a significant role in educating STEM and nonSTEM students in the scientific process and scientific literacy (Grise & Kenney, 2003; Lloyd & Eckhardt, 2010; Marcus, 1993). Similar to community and junior colleges, technical colleges are open-access institutions (Shannon & Smith, 2006). In terms of curriculum and instruction, faculty at community, junior, and technical colleges are “not judged by their research or publishing but on the strength of their ability to help students learn and to engage students with different backgrounds, ethnicities, and aspirations” (Shannon & Smith, 2006, p. 15). While some community colleges may take a more liberal arts approach to education, the mission of technical colleges in the state of Georgia is to provide technical, academic, and adult education that focuses on building a well-educated and competitive workforce (TCSG, 2019). Nonmajors’ Biology I at GTC transfers to other colleges, including two-year and four-year colleges and universities, as part of a statewide articulation agreement (TCSG, 2019). Due to the transferability of Biology I and its similarity to other nonmajors biology courses at two-year institutions, the context of this research may be generalizable to the context of other two-year technical and community colleges. At GTC, Biology I is the science course many students take to fulfill their science-with-lab elective. Biology I attracts students from many programs, including veterinary technology, accounting, bioscience, criminal justice, and construction management. For some students, Biology I may be the only biology class they take in college; for many more, it is the last science class they will ever take.
Historically, before curriculum redesign, the Biology I course at GTC had a low success rates. In the fall of 2015, there were three lecture sections of 115 total students. Course statistics showed that approximately 23% of students withdrew from the course, 35% of students passed with a C or better, and 42% of students failed with a D or F. This brought the overall DFW rate to approximately 65% in the lecture courses. Three instructors decided to work together to reassess how students were being tested and unanimously agreed that an alignment of learning outcomes with assessments and course materials was necessary.
This study considers student success to include course retention and course persistence, as examined as course grades before and after the course redesign. The instructors worked as a team to redesign the GTC nonmajors’ biology course to reflect student needs using the backward design model of the UbD framework. One of the most important components of planning a curriculum using the backward design model is asking why students are learning a particular topic or performing a specific activity (Wiggins & McTighe, 2005). The instructors used this questioning technique to redesign the nonmajors’ Biology I course systematically to promote cohesiveness within the learning goals, assessments, and learning activities of all three sections of Biology I courses. The course redesign began in December 2015 and continued throughout the spring 2016 semester, incorporating changes to Biology I as it was in session.
The methodology described here consists of two parts: a narrative of how instructors used the UbD framework to redesign Biology I, and an explanation of the statistical methods used to analyze and compare course grades before and after course redesign.
The Biology I curriculum was redesigned in the spring 2016 semester by three full-time biology instructors using a collaborative team method guided by the UbD framework. A complete curriculum was already in place for Biology I, with instructor-developed homework and lab assessment questions, test questions, Lecture Notes book (a printed study guide), SoftChalk guides (an eLearning tool embedded in the course Learning Management System, or LMS), and a lab manual. Within the life sciences division at GTC, courses are streamlined, and all instructors teach on a similar schedule and use departmentally developed assessments and tests. Instructors worked together to align course material with the predetermined learning outcomes outlined by the Technical College System of Georgia (TCSG) curriculum for Biology I. Based on the TCSG learning outcomes, instructors reviewed learning goals and course materials, and they collaborated to produce appropriately aligned assessments and resources.
Analysis of the completed course redesign revealed the methods used closely aligned with the backward design model and the UbD framework, as described by Wiggins and McTighe (2005). The method of realignment, outlined in Figure 1, required three main steps: (1) defining goals and unpacking standards, which included identification of learning outcomes and alignment of course competencies; (2) revision of assessments; and (3) revision of student resources.
First, the instructors reviewed the course learning outcomes required by TCSG. In the UbD framework and backward design, instructors must first clarify goals and outcomes for student learning (Wiggins & McTighe, 2005). A brief review of the learning outcomes was performed to determine which outcomes were included or not included in the course materials.
Next, instructors did a horizontal and vertical alignment of the learning outcomes. In this sense, “horizontal” alignment is the alignment of learning outcomes within the course itself; “vertical” alignment is the alignment of learning outcomes in the course with the courses that require it as a prerequisite (Drake, 2012). Instructors held meetings with the course manager for microbiology and the program directors for bioscience and veterinary technology, as their courses required Biology I as a prerequisite. Information gathered on the curriculum and learning outcomes of these courses helped the instructors determine the breadth and depth of the curriculum of Biology I. The aim was to give students a strong foundational knowledge to benefit them in their future science programs and to increase scientific literacy as laypeople.
Afterward, the instructors determined what content was most important and what should be added or removed from the course. Much of the material exceeding the scope of the course and not essential to established goals and learning outcomes were removed or revised. For example, the chapter on DNA replication, transcription, and translation was refocused to include only the most important enzymes and molecules. The content was shifted to a more application-based approach for understanding genetics, the inheritance of traits, mutations, and cancer. Such topics were taught in more depth in the microbiology and bioscience courses.
Next, the instructors used a collaborative team method to review course assessments, including homework and test questions. Each instructor chose chapters of interest within their expertise to redesign and agreed on a schedule to make changes to assessment questions. Each instructor was responsible for editing their section and sending it to the other two instructors for proofreading and final editing. Once all instructors made their edits, the final version of the homework questions was updated in the LMS, and test questions were updated in the test bank software.
Test questions were “Bloomed” using Bloom’s Dichotomous Key (BDK) (Casagrand, 2015; Semsar & Casagrand, 2017). The protocol for using BDK allows the user to assign a test question to one of the six cognitive domains: knowledge, comprehension, application, analysis, synthesis, and evaluation (Crowe et al., 2008; Semsar & Casagrand, 2017). This tool provides scaffolding to reduce bias between raters, allowing more effective categorization of test questions according to the cognitive level (Semsar & Casagrand, 2017).
New tests were made using a testing rubric designed by the three instructors. Rubrics were used to ensure each section of Biology I would have a different version of the test, but with questions made with the input of all instructors, covering the same proportion of each learning outcome, and with questions of the same cognitive difficulty. Tests consisted of 30 multiple-choice style questions and 20 short-answer or essay questions. Each chapter’s learning outcomes were listed on the rubric, and instructors agreed upon the number of questions and Bloom’s level for the questions for each topic. For example, for one chemistry chapter, the instructors identified five learning outcomes, including pH and buffers. Instructors determined that each test would have two questions on pH and buffers; one question would be at the knowledge level and one question at the application level.
Finally, student resources were edited to reflect the material students were required to know per the TCSG learning outcomes and additional outcomes as determined by the instructors after horizontal and vertical alignment. An instructor-written Lecture Notes book was already available for students. It was edited for style and content, while the material was systematically added or removed to complement the revised learning outcomes. Instructor-made exercises through SoftChalk were also edited throughout the semester. The instructors used the same system of editing their assigned chapter’s material before having it proofread and edited by the other two instructors. Instructors updated their lectures and classroom activities while collaborating to share ideas for best practices to strengthen pedagogy. Each instructor created student-learning activities to complement their teaching style. With monthly meetings, the project was completed in five months.
|Percentage of final grades in Biology I.|
All course grades and student information were collected according to college policy using the college LMS. The Office of Institutional Effectiveness provided student data, including demographic information and final course grades. All data were de-identified and were approved for use. Data were analyzed using SPSS and Microsoft Excel. The significance of the independently obtained samples was calculated by performing inference testing about two population proportions, as described by Sullivan (2018). This test was used to test whether or not there is a significant difference between two proportions, or percentages, in two populations (Sullivan, 2018). Calculations were performed using a two-tailed hypothesis at a significance level of p < 0.05. Analysis to evaluate the change in student performance was conducted to compare three sections of classes before curriculum redesign (spring 2015) and after curriculum design (spring 2016).
In spring 2015 (sp2015), there were three sections of Biology I, each taught by one of the three instructors with a total of 102 students receiving grades. In spring 2016 (sp2016), the same instructors taught three sections of Biology I, with 99 students receiving grades. End-of-term data were analyzed to compare the relative frequency of each letter grade. The frequency of each letter grade was used to determine the proportion of students receiving each letter grade before and after the course redesign. The percentage of student grades was compared between sp2015, before the course redesign, and sp2016, after the course redesign (Figure 2).
The change in %A and %B was not significant, but there was a significant increase in %C (sp2015: 14.7%; sp2016: 28.3%), and a significant decrease in %F (sp2015: 19.6%; sp2016: 7.1%). Although there was a decrease in the %W, it was only significant at p < 0.10 (sp2015: 20.6%; sp2016: 14.2%). End-of-term data revealed the overall pass rates (%ABC) in Biology I increased significantly (sp2015: 49%; sp2016: 64.7%). There was a significant decrease in students not passing (%DFW) from 51% in sp2015 to 35.4% in sp2016. Table 1 summarizes the overall change in %A+B, %ABC, %W, and %DFW. The total percentage of withdrawals (%W) includes both withdrawals before midterm (W) and administrative withdrawals (WF).
After the initial evaluation, the instructors were interested in looking at the effects of backward design on various groups of students. They chose to examine traditional-aged college students, beginning college students, and minority students. Traditional-aged students are between 18–22 years old; nontraditional-aged students are under 18 and over 22 years of age. Beginning college students are in their first semester of college, while returning students have one or more semesters of college experience before Biology I. Minority students are individuals who self-identify as nonWhite; because of methods of college data collection, minority students may include students of many national origins. To ensure the observed effects on student groups were not due to a change in demographic data, the instructors compared demographic data at the college as a whole with that of Biology I in sp2015 and sp2016 (Table 2). There were no significant changes in the proportion of various student populations from sp2015 to sp2016.
|Student demographic data.|
Traditional-aged students benefitted more from the course redesign than nontraditional-aged students (Table 3). There was a significant increase in the percentage of traditional-aged students passing the redesigned course in sp2016 (75.5 % from 40% in sp2015) (Table 3). Although there was a decrease in %DFW and an increase in %A+B, neither was significant. There was no significant change in the end-of-term data for nontraditional-aged students (Table 3).
|Comparison of traditional versus nontraditional aged students.|
Data were analyzed for differences based on student experience. The largest observed change occurred in the number of beginning students passing the course (%ABC) after the course redesign, from 25% in sp2015 to 76.2% in sp2016 (Table 4). Statistical analysis showed that beginning students had a significant increase in %A+B and %ABC, and a significant decrease in %DFW (Table 4).
|Comparison of beginning versus returning students.|
Before the course redesign in sp2015, there was no significant difference between the proportion of minority and nonminority student grade frequency (Table 5). Minority students, however, had a greater %W and %DFW than nonminority students before the redesign. After the course redesign in sp2016, minority students showed a significant increase in %ABC and a decrease in %DFW, with no significant difference in %A+B and %W. From sp2015 to sp2016, nonminority student performance remained relatively constant, with no significant difference in the proportion of grades. Black and African American students had the largest significant increase in %ABC than any other group (Table 6) with the largest gains in %C (sp2015: 14.8%; sp2016: 40.6%). There was also a significant decrease in the percentage of Black and African American students withdrawing from or failing the course (Table 6).
|Comparison of minority versus nonminority students.|
|Grade percentages for Black and African American students.|
This study reports the course redesign of a nonmajors biology course using the backward design model as prescribed by UbD at Gwinnett Technical College (Wiggins & McTighe, 1998, 2005). The historically high DFW rate prior to the course redesign necessitated the restructuring and realignment of the course. This curriculum redesign led to a significant increase in pass rates in spring 2016 (Figure 2). This aligns with other studies showing increases in student retention after using various methods to redesign their undergraduate nonmajor STEM courses (Lloyd & Eckhardt, 2010; Minbiole, 2016; Roberts et al., 2018). After the course redesign of the curriculum, all three Biology I instructors reported more time in lecture for class discussions and activities. This may have played a role in the increase in students’ pass rates, which was also seen in Minbiole’s (2016) backward design of a nonmajors biology class. Similar to Lloyd and Eckhardt (2010), a significant increase in the number of students earning a grade of A or B was not observed; however, there was a significant increase in the number of students earning a C (Figure 2). These results mirror those of Lloyd and Eckhardt (2010), indicating the course redesign had a positive effect on students who were at risk of failing or withdrawing from the course. This study also revealed the inequality of the DFW rates for traditional-aged students, first-time beginning students, and minority students. Similar to the course redesign of Roberts et al. (2018), this course redesign led to significant improvements in these demographic groups and narrowed the achievement gap. The increase in pass rates in this nonmajors’ biology course could not only help students matriculate through their programs, but could also help improve their overall attrition rate, as attrition rates for students in two-year colleges are typically higher compared to four-year colleges (Summers, 2003). The finding of increased pass rates for first-time beginning students is also significant, as attrition rates for this demographic group are higher (Drew, 1990; Summers, 2003).
The improvement in the Black and African American student success rate after the course redesign is very promising for the overall retention of this at-risk student population. The open-door nature of two-year colleges provides access for minority populations to pursue college (Shannon & Smith, 2006; Smith & Vellani, 1999), with minority students (Black and Hispanic) making up 37% of the students in 2018 enrolled in community college for credit (AACC, 2018). However, the achievement gap between minority and White students in postsecondary education has been well documented, and even the minority students are less likely to finish their postsecondary degree as compared to White students (Carter, 2006). Furthermore, there are achievement gaps persisting in math and science regarding Black and African American students (Anderson & Kim, 2006; Lorah & Ndum, 2013). Even though there are many factors that lead to the attrition of Black and African American students in postsecondary education, this study has shown how an effective course redesign can have a positive impact on this group.
Increasing the number of students successfully passing STEM courses at the two-year college level can also have an impact on increasing the number of students that eventually pursue and persist in four-year STEM degrees (Bahr et al., 2017; Snyder & Cudney, 2017). This is beneficial, as there is a continued need for more STEM-trained workforce to match the demand of the science and technology jobs in the 21st century (PCAST, 2012). As many students start their college education at either the community college or technical college (McIntosh & Rouse, 2009), two-year colleges are uniquely placed to have a positive impact on increasing the number of STEM-trained and STEM-informed students. It is also during the first two years in either a two-year or four-year college where curriculum changes are the most effective in retaining students in STEM (PCAST, 2012). Increasing the learning and retention in STEM courses in either the two-year or four-year college level has downstream benefits in K–12 education (Alberts, 2005; PCAST, 2012).
Overall, this study demonstrates how using the backward design model can be effective in increasing student learning and retention in biology at the technical college level. As there are several national “call-to-action” initiatives to reform STEM education at the postsecondary level to enhance student learning and persistence in STEM (AAAS, 2009; NRC, 1999; PCAST, 2012), the backward design model is one option to modify existing science curriculum. Also, as the use of backward design in remodeling K–12 curricula has been well established (Brown, 2004), this study adds to the body of work in using backward design in changing postsecondary curricula. This study contributes to the evidence that curriculum redesign helps students who were at risk of failing or withdrawing, which is an alignment with other curriculum redesigns targeted for at-risk students (Kamler & Comber, 2005). Lastly, our research adds to the limited, but growing body of research regarding designing STEM curriculum at the technical college level.
The first and second authors contributed equally to the preparation of the manuscript.
Margaret Long (firstname.lastname@example.org) is division chair of life sciences at Gwinnett Technical College in Lawrenceville, Georgia. Adrienne Cottrell-Yongye (email@example.com) is an assistant professor of biology at Georgia Gwinnett College in Lawrenceville, Georgia. Tyler Huynh (firstname.lastname@example.org) is a biology instructor at Gwinnett Technical College in Lawrenceville, Georgia.
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