Inclusive Pedagogy: Teaching Methodologies to Reach Diverse Learners in Science Instruction

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Equity & Excellence in Education, 40: 252–265, 2007Copyright c© University of Massachusetts Amherst School of EducationISSN 1066-5684 print /1547-3457 onlineDOI: 10.1080/10665680701434353

Inclusive Pedagogy: Teaching Methodologies to ReachDiverse Learners in Science Instruction

Mary A. Moriarty

This study used quantitative and qualitative methods to examine the use of inclusive pedagogy by science, technology,engineering, and mathematics (STEM) faculty at three community colleges. The purpose was to identify barriers to theadoption of inclusive teaching methods for diverse learners and students with disabilities and to propose ways to breakdown these barriers. Two hundred and eleven community college STEM faculty members in Western Massachusettswere sent a questionnaire that was administered electronically, and 11 faculty members were interviewed, 9 of whomalso were observed in the classroom. The most significant among the barriers reported were the lack of an inclusivemindset, lack of knowledge about pedagogy, high teaching loads, and lack of time for instructional development.Implications for practice and research are discussed.

Over the last few years considerable attention has beengiven to the need for educating a diverse workforce in sci-ence, technology, engineering, and mathematics (STEM).Reports from the National Science Foundation (NSF;1996, 2000, 2004) have stressed the critical importance ofSTEM education and identified women, minorities, andindividuals with disabilities as being underrepresentedin STEM fields. Individuals with disabilities are amongthe most marginalized of these groups (Wolanin & Steele,2004) and face significant obstacles and barriers to access-ing higher education STEM programs (Burgstahler, 1994;NSF, 2000). Identification and elimination of these barri-ers are critical to the success of students with disabilitiesin postsecondary education, particularly in communitycolleges, since this is where many students with disabil-ities begin their postsecondary education (Hall & Belch,2000; National Center for Educational Statistics [NCES],2000).

The paradigm that has dominated the treatment ofdisability both within society and within higher educa-tion has emanated from a theoretical approach that looksat disability from a medical perspective (Marinelli & DellOrto, 1999). More recently, researchers have begun tolook at disability from a social theory perspective (Hahn,1999), which allows us to think about disability in a newway and opens avenues for more inclusive teaching andlearning.

Address correspondence to Mary A. Moriarty, Springfield Techni-cal Community College, One Armory Square, Springfield, MA 01102.E-mail: [email protected]

Change in the way society views disability coincideswith recommendations about science instruction. Re-forms in science education (National Research Center[NRC], 2001, 2003a) and research on diverse learners(Dunn & Waggoner, 1995; Gardner, 1999; Sternberg &Grigorenko, 2002) have contributed to recommendationsfor changes in instruction to meet the needs of a widerrange of learner types.

THEORETICAL PERSPECTIVES ANDRELATED RESEARCH

The Nature of Diverse Learners

In the past few years, educational researchers havepaid considerable attention to the way traditional formsof college instruction have perpetuated a model thatviews disability in a negative light and places the bur-den for learning and accommodation on the individualrather than on the system. As we begin to move to amore social responsibility framework for thinking aboutdisability, we begin to see individuals with disabilitiesas falling within a range of different types of learners.Researchers have challenged traditional views of intelli-gence and learning as one-dimensional concepts used tomeasure all learners and have conceptualized learningin new ways. For example, Gardner (1999) indicates thatnew educational paradigms have altered the conceptu-alization of intelligence so that we can no longer lookat either intelligence or learning from just one perspec-tive. The research in the areas of multiple intelligence

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REACHING DIVERSE LEARNERS IN SCIENCE INSTRUCTION 253

(Gardner, 1999), learning styles (Dunn, Griggs, Olson,Beasley, & Gorman, 1995; Dunn & Waggoner, 1995;Kolb, 1984; Miglietti & Stranger, 1998; Sarasin, 1995),and brain-based learning (Bransford, Brown, & Cocking,1999) share a common belief in the diversity of learners.Of growing concern is the possibility that the teachingpractices at our colleges and universities do not effec-tively serve students with non-traditional learning pro-files (Sternberg & Grigorenko, 2002).

STEM Instruction in Higher Education

Much of the research on learning and pedagogy hasled to a reformulation of the traditional ways we thinkabout teaching. This is particularly true for the sciences,where considerable research has focused on understand-ing how students learn (NRC, 2001, 2003a). Traditionalundergraduate science instruction has tended to con-strue science teaching as the transmission of knowledgethrough the delivery of information from faculty to stu-dent (Taylor, Gilmer & Tobin, 2002). Through a lectureformat, the faculty member would transmit discipline-related information, while the student would obtainknowledge through listening and recording. The role ofthe learner in this context is seen as passive and priorlearning and world experience are de-emphasized. Morerecent research has emphasized the need for learnerparticipation and engagement in the learning process(American Psychological Association, 2002; NRC, 2001,2003a). Teaching practices that focus on the student’s con-struction of knowledge are seen to be more effective inthe development of science literacy (NRC, 2001, 2003a).

Reform efforts have placed a strong emphasison teaching practices that foster interactive, learner-centered approaches. The National Science EducationStandards (NRC, 2003b) act as a guideline for effectivescience instruction and emphasize that science is for allstudents, regardless of age, gender, ethnic background,or disability. Science is an active process that engagesthe learner both mentally and physically, and scientificinquiry becomes a central tenant of science learning.

Techniques Applicable for Studentswith Disabilities

National reform efforts have placed a strong empha-sis on the importance of recognizing different patternsof ability and have advocated for inclusive pedagogicalapproaches for all students, including those with dis-abilities. Fortunately, the advent of Universal Design forLearning (UDL) has provided a model that incorporatesinclusion as the center of instructional practice. In thelast few years, theorists have begun to take a seriouslook at UDL as a model, which incorporates an under-standing of diverse learners and promotes inclusive ped-agogy (Rose & Meyer, 2002). UDL shifts the perceptions

about students with disabilities so that all students areseen as falling on a continuum of learners with differ-ences in learning styles and strengths (Meyer & O’Neil,2000). The move to UDL represents a major paradigmshift from treating people with disabilities as part of amedical model needing specialized care to a model inwhich everyone is treated as an individual with varyingstrengths and learning preferences (Sandhu, 2000).

Progress in STEM Instruction

Overall, the research on instructional methods in post-secondary education indicates that faculty, particularlyfaculty in science and engineering, continue to rely ona traditional lecture format for instruction, regardlessof evidence that indicates students will be more satis-fied with their learning and achieve more with learner-centered approaches (Kardash & Wallace, 2001; NCES,2002; Peterson, 2003; Seymour & Hewitt, 1997; Walczyk& Ramsey, 2003). Since the majority of the researchconducted was done at four-year colleges very little in-formation is available concerning adoption and imple-mentation of reformed practices or UDL in communitycolleges, which enroll the greatest diversity and numbersof students with disabilities (NCES, 2000). The absenceof research in two-year colleges is noteworthy for severalreasons. First, one of the defining characteristics of thecommunity college is its vision of itself as a teaching col-lege (Grubb, 1999). Therefore, one might speculate thatthere would be a greater interest in innovative teach-ing strategies. Second, two-year colleges tend to havehigher percentages of students who are women, minori-ties, and persons with disabilities (NCES, 2000). Many ofthese students learn in non-traditional ways and couldbenefit from more innovative instruction (Sternberg &Grigorenko, 2002). Third, nearly one half of all under-graduates with disabilities are enrolled in two-year col-leges (NCES, 2000), indicating a greater need and per-haps a greater demand for pedagogical methods thatwill effectively reach these students. The available lit-erature reveals little about the possible implementationof reformed practices in community colleges. However,the literature does suggest that there are considerableobstacles to implementing these instructional changes inhigher education in general.

Among faculty at four-year institutions, a number ofpractical, attitudinal, and environmental barriers existthat prohibit the adoption of innovative and inclusivepedagogy (Jensen, McCrary, Krampe & Cooper, 2004;Silver, Bourke, & Strehorn, 1998; Sunal et al., 2001). Bar-riers, such as class size, time, assumptions about teach-ing and learning, knowledge about pedagogy, and col-lege resources and supports, all have significant impacton teaching. Community college faculty members mostlikely face similar barriers. However, the focus on teach-ing in the two-year college, the differences in responsi-bilities between two- and four-year college faculty, and

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254 MARY A. MORIARTY

the differences in the types of students enrolled may allserve to mandate a very different pedagogical environ-ment. The review of literature supports the need for ad-ditional research in the area of inclusive pedagogy inSTEM, particularly in two-year colleges.

METHODOLOGY

Research Design

The purpose of this multi-site case study was twofold:(a) to identify barriers to the adoption of existing inclu-sive teaching methods by STEM faculty in the commu-nity college environment, and (b) to propose ways tobreak down these barriers, thus leading to increased useof such teaching methods. The case study incorporateda sequential method, which was used to obtain quanti-tative and qualitative results from a sample of commu-nity college faculty. This method as defined by Creswell(2003) begins with quantitative methods to seek a broadbase of information and is followed by qualitative meth-ods to gain a more in-depth understanding.

Consistent with the case study approach, the focus ofthis study was an in-depth understanding of communitycollege STEM faculty from three selected community col-leges in western Massachusetts. Data collection methodsincluded a questionnaire, interviews, observations, anddocument analyses. The use of multiple data collectionmethods provides triangulation and helps to ensure thatthe researcher looks at the phenomenon and context tothe fullest extent possible (Rossman & Rallis, 2003).

Limitations

There are two major limitations specific to the casestudy method. First, the case study method is contextdependent; as such, conclusions cannot be generalizedto other situations (Rossman & Rallis, 2003). Second,the case study is considered to be interpretive research(Creswell, 2003). As such, there is a danger of resultsbeing impacted by researcher bias or subjectivity (Mer-riam, 1998). However, maintaining rigor in data collec-tion and analysis, as well as obtaining ongoing feedbackfrom other professionals, can minimize the effect of re-searcher subjectivity. Rossman and Rallis (2003) recom-mend a number of strategies for insuring that a studyis credible and rigorous. Among the strategies that wereemployed in this study are audit trails documenting theprocess of gathering, analyzing, and interpreting data;member checks for participant verification; and the useof multiple methods of data collection and analysis.

Research Questions

The following questions formed the basis of thisstudy: (1) What are the current teaching styles and meth-

ods of curriculum delivery used by community collegeSTEM faculty? (2) What are the levels of awarenessand knowledge of community college STEM facultyabout inclusive teaching practices? (3) What are thepersonal, attitudinal, and environmental factors thatinhibit community college STEM faculty from usinginclusive pedagogical practices to serve students withdisabilities and other diverse learners?

Site and Participant Selection

Three community colleges in western Massachusettswere selected for the multi-site case study, which allowedfor a purposeful sample of approximately 211 full andpart-time instructors from STEM disciplines. Of the 211STEM faculty members, 11 were selected for interviews,and 9 were also observed in their classrooms.

DATA COLLECTION, MEASUREMENT,AND ANALYSIS

Quantitative

Survey instrument. A questionnaire was developedto collect data about the instructional techniques, teach-ing approaches, and barriers to the adoption of inclu-sive pedagogy by community college STEM faculty. Theinstrument was specifically designed for the study andwas, in part, a modification of several questionnairesused in similar studies. Stefanich and Norman’s (1999)survey of faculty attitudes, Walczyk and Ramsey’s (2003)survey of innovative instructional practices in scienceinstruction, and Sunal and associates’ (2001) survey offaculty inquiry-based teaching practices were used asmodels for item selection. Research on the barriers toimplementing inclusive pedagogy in four-year collegesalso was used to develop questionnaire items.

The questionnaire was self-administered via a web-site, was cross-sectional, and contained many items thatwere based on a Likert scale. The instrument was for-mally pilot tested in May of 2005 with a group of 12health division faculty at Springfield Technical Commu-nity College, and modifications were made based ontheir input and responses. Following the pilot test andmodification the questionnaire was administered elec-tronically to 211 STEM faculty members currently work-ing at the three community colleges. The survey returnrate was 72% (n = 152). Table 1 shows the demographicsof the participants at all three campuses.

The three campuses are very different in size, geo-graphic location, and academic focus. Despite these dif-ferences the overall demographics of faculty are verysimilar, which provides a greater level of confidence inthe generalizability of results.

Quantitative data analysis was used to evaluatedata collected through the questionnaires. Questionnaire

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Table 1Demographics of survey respondents

Characteristic Response (n) Response (n) Response (n) Response (n)

Gender Male (74) Female (77) Other (1)Ethnicity White (139) Latino (2) Asian (6) Other (4)Teaching Status Full time (87) Part time (64) Not reported (1)Educational Level Associates (3) Bachelors (11) Masters (101) Doctorate (37)Age 20 to 35 (18) 36 to 50 (61) 51 to 65 (73)

responses were recorded in Microsoft Excel and ana-lyzed using SPSS statistical software. A number of sta-tistical methods were used to analyze data. Factor anal-ysis was used to discover patterns in the relationshipsamong variables and to reduce data to a manageablesize. In order to answer the research questions, descrip-tive statistics and frequencies were calculated for eachvariable, and correlations among variables were deter-mined. Multiple regression analysis was used to deter-mine the relationships between the dependent and inde-pendent variables. Table 2 describes the definitions forall the variables used in the analysis.

Qualitative

Interviews and observations. In addition to the quan-titative method, a qualitative method was used to ob-tain more in-depth information regarding instructionalpractices, beliefs, and barriers to implementing inclusivepractices. The final qualitative sample consisted of 11 fac-ulty who agreed to be interviewed, 9 of whom were alsoobserved in the classroom setting. The interview sampleconsisted of faculty who teach Anatomy and Physiol-ogy, Biology, Physics, Chemistry, Developmental Alge-bra, Calculus, Computer Information Systems, and En-gineering. Each of the 11 faculty participants was for-mally interviewed for approximately one hour. Initialquestions were designed to reflect the research ques-tions and fell into three categories: teaching methods andstrategies, attitudes and perceptions, and barriers to im-plementing inclusive instruction. Questions had been re-viewed by a panel of three STEM faculty members priorto the commencement of the qualitative portion of thestudy and were modified based on their input.

Nine of the 11 participants interviewed were observedin the classroom in order to gain additional informa-tion about teaching techniques. Observations served pri-marily as a source of data triangulation and verification.An observation guide was developed based on the fol-lowing: an observation checklist compiled by Merriam(1998), the Reformed Teaching Observational Protocoldeveloped at the University of Arizona (Lawson, 2002),and the STEMTec–Core Evaluation Classroom Observa-tional Protocol adopted by Berger (Sireci, Zanetti, Slater,& Berger, 2001). The observation instruments were mod-

ified to include observation criteria that relates to Uni-versal Design.

Data were collected from interviews, observations,questionnaires, and related artifacts. The constant com-parative method developed by Glaser and Strauss (1967)was used to analyze data. This method encourages thegradual development of categories, subcategories, andthemes through a process of analysis that begins withthe initial collection of data. The data, once broken downand sorted into categories and subcategories, were usedfor theme development.

QUANTITATIVE RESULTS

Factor Analysis

Key variables of interest in this study include ques-tionnaire items that relate to instructional practices,knowledge about pedagogical approaches, and attitudesand beliefs about teaching and learning. In order to de-velop a more meaningful set of indicators, factor anal-ysis was used to group questionnaire items into relatedscales. Factor analysis is a technique that identifies com-mon patterns and associations that can be used to groupmany variables so as to maximize in-group commonalityand between-group variability. The items used in the ex-ploratory factor analysis were rotated orthogonally, us-ing the varimax method,1 2 resulting in variable dimen-sions within each category. Some items were droppedas the result of conducting a reliability analysis usingCronbach’s alpha to determine strength of reliable as-sociation among grouped variables. Factor analysis re-sulted in nine instructional practices, six beliefs aboutteaching and learning, and two environmental factors(See Table 3).

Descriptive Statistics

The first two research questions ask about the cur-rent teaching practices and level of awareness concern-ing inclusive teaching practices of community collegeSTEM faculty. Descriptive statistics provide a means forexamining the range and level of use of different instruc-tional practices as well as an analysis of the relationshipbetween variables. Frequencies, means, and standard

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Table 2Variable definitions with means and standard deviations1

Variable Name Variable Definitions

Personal CharacteristicsSubject (SCIENCE) Single item identifying subject currently taught (1 = Science, 0 = All else)

Science = 40%Subject (TECH) Single item identifying subject currently taught (1 = Technology, 0 = All else)

Technology = 24%Subject (MATH) Single item identifying subject currently taught (1 = Mathematics, 0 = All

else) Mathematics = 25%Status: Full-Time (STATF) Single item indicating employment status (1 = Full-time, 2 = Part-time)

Full-time = 57%Degree (DEG) Single item indicating highest degree obtained (1 = Associates or Bachelors,

2 = Masters or Doctorate) Masters or Doctorate = 91%Gender: Male (GENM) Single item identifying gender (1 = male, 2 = female) Female = 51%

Environmental FactorsTime for Instructional Development

(TIMDEV)Three item scale that describes institutional factors that limit innovation

Standardized alpha reliability = .56, Mean = 10.93, SD = 2.34Institutional Resources (INSRES) Three item scale that describes institutional support and resources

Standardized alpha reliability = .59, Mean = 10.67, SD = 2.27Attitudes and Beliefs

Inclusive Mindsets (INCMIN) Eight item scale indicating a propensity towards inclusive thinkingStandardized alpha reliability = .78, Mean = 28.01, SD = 4.30

Technology Comfort Level (TECCL) Four item scale describing the level of comfort with technology useStandardized alpha reliability = .78, Mean = 16.58, SD = 3.57

Teacher Responsibility (TERES) Three item scale describing beliefs about faculty responsibility Standardizedalpha reliability = .59, Mean = 9.38, SD = 2.17

Pedagogical Competency (PEDCOM) Two item scale that indicates self-assessed participation and knowledge ofpedagogy. Standardized alpha reliability = .62, Mean = 8.23, SD = 1.54

Need for Change (NECH-I) (NECH-D) Two single items indicating beliefs about the need for change (1 = StronglyDisagree to 5 = Strongly Agree) Institutional – Mean = 3.86, SD = .966Discipline – Mean = 3.16, SD = 1.10

Instructional PracticesTechnology Utilization (TECUTIL) Six item scale describing ways in which technology is used to enhance

instruction Standardized alpha reliability = .82, Mean = 18., SD = 6.03Varied Presentation Strategies (VPRESTR) Two item scale describing techniques that are used to reach different types

of learners Standardized alpha reliability = .58, Mean = 7.87, SD = 1.80Interactive Learning (INTLERN) Two item scale describing student participation and interaction in class

Standardized alpha reliability = .71, Mean = 6.79, SD = 2.19Student Engagement (STUENG) Four item scale describing ways in which student interest and connection to

learning are fostered Standardized alpha reliability = .62, Mean = 14.16,SD = 3.77

Diversified Instruction (DIVINST) Three item scale describing techniques used for different learner typesStandardized alpha reliability = .56, Mean = 9.6, SD = 2.92

Traditional Teaching (TRATEA) Single item indicating class time used primarily in a lecture format (1 = Neverto 5 = Almost Always) Mean = 3.17, SD = 1.15

Alternative Assessment (ALTAS) Single items indicating alternatives in the way students express what theyknow (1 = Never to 5 = Almost Always) Mean = 3.64, SD = 1.31

Pedagogical Variety (PEDVAR) Six item scale indicates use of a variety of innovative pedagogicalapproaches Standardized alpha reliability = 8.23, Mean = 21.8, SD = 5.20

Multimedia Instruction (MULINST) Single item scale indicates level of use of multimedia instruction. (1= I havenever heard of it, to 5 = I know what the approach is and I use it on aregular basis) Mean = 3.72, SD = 1.15

deviations for the variables were calculated in orderto further examine the nine instructional practices, sixbeliefs about teaching and learning, and two environ-mental factors. In order to provide a meaningful com-parison, each scale mean was adjusted by combiningthe indicated questionnaire items and calculating thecombined mean. Each of the scales was categorized intopractices, beliefs, and environmental factors in order toconform to the research questions and theoretical frame-

work. Table 3 shows the adjusted mean and standarddeviations of the scales.

An examination of the practices data in Table 3 showsthe use of practices to be within a standard distribu-tion; varied presentation strategies, interactive learning,alternative assessment, pedagogical variety, and multi-media instruction are slightly skewed in a positive di-rection, indicating a trend toward higher reported useof those practices. Varied presentation strategies with a

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Table 3Adjusted means and standard deviations forinstructional practices, beliefs and environmental scales

Practices Mean SD

Varied Presentation Strategies 3.93 .90Multimedia Instruction 3.71 1.15Alternative Assessment 3.63 1.30Pedagogical Variety 3.63 .86Interactive Learning 3.40 1.09Diversified Instruction 3.22 .97Traditional Teaching 3.17 1.15Technology Utilization 3.13 1.00Student Engagement 3.08 .77Beliefs

Technology Comfort Level 4.14 .89Pedagogical Competency 4.11 .77Inclusive Mindset 3.99 .62Need for Change – Institution 3.85 .97Need for Change – Discipline 3.16 1.10Teacher Responsibility 3.12 .72

Environmental FactorsTime for Instructional Development 3.64 .78Institutional Resources 3.55 .76

mean of 3.93 shows the highest reported use within thiscategory. Varied presentation strategies include present-ing material in multiple ways and using hands-on in-structional aids in class. The traditional teaching scalehas a mean of 3.17 with 42% of respondents indicat-ing that the class period is spent primarily in a lectureformat.

The alternative assessment scale with a mean of 3.63requires further examination. A first glance would leadto the conclusion that 57% of STEM faculty providedalternatives (such as portfolios, projects, exams, and pre-sentations) in the way in which students express whatthey know. However, a closer examination of frequen-cies on other questionnaire items reveals that traditionalforms of assessment are most commonly used. For ex-ample, 89% of respondents indicated that exams are fre-quently or always used as assessment, while 56% indi-cated that projects were frequently or always used. Pa-pers were used by 37% of the respondents and port-folios were used by only 19% of STEM faculty. Thefindings suggest that even though 57% of STEM fac-ulty members indicate that they provide alternatives,the alternatives consist primarily of exams, followedby projects. The finding suggest a predominate use oftraditional forms of assessment used by these facultymembers.

A similar pattern of distribution is shown within thebeliefs category with many of the distributions slightlyskewed in a positive direction, indicating a trend to-ward agreement with those beliefs. Technology comfortlevel and the pedagogical competency show the high-est means, followed by inclusive mindset and need forchange – discipline. Technology comfort level presents

the most interesting pattern with 35% of respondentsreporting a strong agreement, while the remainder ofthe respondents distributed across the remainder of themeans in relatively small percentages.

The inclusive mindset scale is made up of a combinedset of beliefs that relate to the desire and willingnessto adopt methodological approaches that are inclusiveof diverse learners in general and students with dis-abilities in particular. A positive skew is indicative of atrend toward embracing those beliefs. Within this scale,frequencies showed that 78% of respondents indicatedthey agree or strongly agree that they are receptive tomaking changes to accommodate students with disabil-ities, and 75% agree that students with disabilities arecapable of learning the material in their class. Respon-dents also agree that they try to match their teachingstyles to accommodate students’ learning needs (74%),and they agree that they continually look for better waysto teach and are open to new forms of instruction (88%).Pedagogical competency relates to the belief that one isknowledgeable about different teaching approaches andthat actions have been taken to improve teaching skills.Over 79% of the respondents indicated that they agree orstrongly agree that they are knowledgeable about differ-ent teaching practices, and 82% agree or strongly agreethat they have taken part in workshops that relate toteaching.

The final scales indicate dimensions of environmentalfactors. The two dimensions, time for instructional de-velopment and institutional resources, also fall within anormal distribution with slight positive skews, indicat-ing a slight trend toward beliefs that relate to having timeto develop new teaching approaches and the resourceswith which to do so.

Correlation and Regression Analysis

The third research question asked what the personal,attitudinal, and environmental factors are that inhibitcommunity college STEM faculty from using inclusivepedagogical practices. Correlation and regression anal-ysis was used to address this question and to determinethe relationship among the variables. The degree vari-able was collapsed in order to provide dichotomous vari-ables for further analysis since an analysis of frequen-cies showed little variability between the responses ofrespondents who indicated masters and doctorate de-grees. In addition, an examination of frequencies showedlittle difference between the responses across campuses.Therefore, the campus variable was not included in theanalysis. Future research may reveal some existing dif-ferences across campuses.

A few correlations are noteworthy. Of particular in-terest are the correlations between beliefs and instruc-tional practices. For example, inclusive mindset is pos-itively correlated with eight of the nine instructional

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practices (technology utilization, varied presentationstrategies, interactive learning, student engagement,diversified instruction, alternative assessment, pedagog-ical variety, and multimedia instruction) at a .01 level ofsignificance. Inclusive mindset is negatively correlatedwith traditional teaching (also with a p < .01).

Similarly, technology comfort level is positively corre-lated with seven of the nine instructional practices (tech-nology utilization, varied presentation strategies, diver-sified instruction, alternative assessment, and multime-dia instruction with a p < .01 while student engagementand pedagogical variety correlated at the .05 level ofsignificance). Pedagogical competency also is positivelycorrelated with eight of the nine instructional practices(varied presentation strategies, student engagement, di-versified instruction, and multimedia instruction [p <

.01] and technology utilization, interactive learning, al-ternative assessment, and pedagogical variety [p < .05]).Pedagogical competency is negatively correlated withstatistical significance of p < .01 with traditional teach-ing. Interactive learning (p < .01) and alternative assess-ment (p < .05) also are negatively correlated with tradi-tional teaching.

An examination of the correlations3 suggests thatthere is a significant relationship among beliefs aboutteaching and learning, the use of traditional methods,and the actual provision of more innovative instructionalpractices. The correlation matrices were used to formu-late the regression analysis that will be discussed in moredetail in the next section.

Table 4Results of regression analysis with practices as dependent variables

Variables TECUTIL VPRESTR INTLERN STUENG DIVINST TRATEA ALTAS PEDVAR MULINSTPersonal β β β β β β β β B

SCIENCE −.31∗∗ −.15 −.34∗ −.11 −.22 .03 −.16 .05 −.11TECH .17 −.04 −.06 −.02 −.04 −.32∗∗ −.07 −.07 .07MATH −.31∗∗ −.32∗ −.11 −.10 −.21 −.20 −.24 .07 −.31∗∗STAT .12 −.01 .11 .04 −.18 .10 .16 .26∗∗ .15DEG −.04 −.06 −.00 .06 −.03 −.11 −.03 .05 .08GEN (M) −.13 −.06 −.08 −.14 −.16 .09 −.17∗ −.03 −.15∗AGE −.10 −.00 −.10 −.01 −.01 .04 −.14 −.11 −.02R2 .25∗∗∗ .07 .09∗ .03 .07 .13∗∗ .10∗∗ .10∗ .15∗∗∗Environmental

Timdev .13 .32∗∗∗ .32∗∗∗ .38∗∗∗ .10 −.28∗∗∗ .09 .40∗∗∗ .15Insres .01 .06 −.06 .01 .10 .02 .01 .02 .02R2 .02 .11∗∗∗ .09∗∗ .13∗∗∗ .02 .07∗∗ .01 .15∗∗∗ .02

BeliefIncmin .01 .30∗∗∗ .15∗ .26∗∗ .17∗ −.20∗∗∗ .21∗ .21∗∗ .24∗∗Teccl .51∗∗∗ .15∗ −.02 .08 .09 −.06 .20∗ −.08 .36∗∗∗Teres .07 .07 .09 .15 .23∗∗ .06 .11 .15 .03Pedcom .05 .01 .14 .14 .24∗∗ −.08 .02 .44∗∗∗ .07NECH-I −.02 −.15 −.17 −.04 .01 .01 .07 .00 .13∗NECH-D −.03 .24∗∗ −.19∗ −.04 −.05 −.01 −.10 −.15∗ .12R2 .22∗∗∗ .17∗∗∗ .14∗∗∗ .12∗∗ .17∗∗∗ .05∗∗ .11∗∗ .31∗∗∗ .21∗∗∗

Total R2 .48∗∗∗ .35∗∗∗ .32∗∗∗ .29∗∗ .26∗∗∗ .25∗∗∗ .22∗∗ .56∗∗∗ .38∗∗∗

∗ p< .05; ∗∗ p< .01; ∗∗∗ p< .001;

Multiple Linear RegressionMultiple linear regression was used to identify the

relationship between dependent and independent vari-ables. A blocked hierarchical ordinary least squared mul-tiple regression was used to identify the predictive rela-tionship between these variables. Instructional practicesand attitudes and beliefs were identified as dependantvariables. A regression analysis was run for each prac-tice as a dependent variable using personal characteris-tics, beliefs, and environmental factors as independentvariables. A regression analysis also was run with eachbelief as a dependent variable and with personal charac-teristics and environmental factors as independent vari-ables. Each of these variables will be discussed sepa-rately. However, it is important to note that the total R2

values for each of the practices values are within a sig-nificant range (p < .01 and p < .001) indicating that theoverall model fits the data. Similarly, the total R2 valuesfor four of the six belief variables show that the model isa good fit for the data at a .01 significance level. Resultsof the regression analysis are reported in Tables 4 and 5below.

The regression analysis indicates some interesting re-lationships. For example, the individual variable Betavalues indicated varied presentation strategies has sev-eral important predictors. Inclusive mindset (p < .001),technology comfort level (p < .05), and need for change –discipline (p < .01) are all positively associated with var-ied presentation strategies. These findings suggest thatfaculty members who have more inclusive beliefs and

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Table 5Results of regression analysis with beliefs as dependent variables

Variables INCMIN TECCL TERES PEDCOM NECH-I NECH-DPersonal β β β β β B

SCIENCE .01 −.12 −.32∗∗ .06 .19 .04TECH .09 .09 −.09 .06 −.07 .07MATH .02 −.49∗∗∗ −.39∗∗ .00 .06 .06STAT .05 −.00 −.30∗∗∗ .13 .10 .09DEG .01 −.03 .01 .24∗∗ −.19∗ −.05GEN (M) −.08 −.14 .01 -.10 .01 −.12AGE −.12 −.05 .01 .10 .13 .21∗

R2 .03 .26∗∗∗ .14∗∗ .13∗∗ .07 .06Environmental

TIMDEV .50∗∗∗ .10 .08 .28∗∗∗ .04 .13INSRES .07 .01 .08 .19∗∗ .11 .02R2 .25∗∗∗ .01 .02 .12∗∗∗ .02 .02Total R2 .28∗∗∗ .27∗∗∗ .16∗∗ .26∗∗∗ .09 .08

∗ p< .05, ∗∗ p<. 01, ∗∗∗ p< .001.

who are comfortable with technology are more likely touse presentation strategies that include presenting ma-terial in multiple ways to reach a variety of learners,including the use of technology. Time for instructionaldevelopment (p < .001) also is a very significant predic-tor of varied presentation strategies, interactive learning,student engagement, and pedagogical variety indicatingthat having the time to develop new instructional materi-als is critical to the use of these methods in the classroom.

In addition, inclusive mindset and need for change –discipline (p < .05) are significant predictors of interac-tive learning. Faculty members who have a more inclu-sive mindset are more likely to use interactive strategies.Faculty members who believe that no change in their dis-cipline is needed are less likely to use interactive learningstrategies. Inclusive mindset (p < .01) also is significantlyassociated with and predictive of student engagement,pedagogical variety, and multimedia instruction, whichindicates that inclusive beliefs lead to increased engage-ment of students in the learning process and the use of avariety of approaches to reach students.

Consistent with the above analysis, traditional teach-ing is negatively associated with inclusive mindset (p <

.001), technology instruction (p < .01), and time for in-structional development (p < .001). These predictorssuggest that faculty who report lower levels of inclusivebeliefs and those that report that they do not have timeto develop new teaching methods due to discipline or toadministrative responsibilities are more likely to teachusing a traditional lecture format.

Personal factors accounted for the smallest amountof variance among all the variables, particularly withinthe belief scales. No personal factors are predictive of in-clusive mindset or need for change — discipline. High-est degree (p < .01) is predictive of pedagogical com-petency, suggesting that those with either a masters ordoctorate degree are more likely to report knowledge

about different teaching approaches. However, the num-ber of respondents (n = 14) with associates or bache-lors degrees was so small that making comparisons isnot meaningful. As was the case in the practices cate-gory, math instruction is negatively associated with anumber of the beliefs, technology comfort level (p <

.001), and teacher responsibility (p < .01), suggestingthat math faculty tend to be less comfortable with tech-nology and perhaps feel less responsible for the successof students in their classes. This finding is consistent withfindings within the practices scales in which math in-struction has a negative association with technology uti-lization (p < .01), presentation strategies (p < .05), andmultimedia (p < .01). Science instruction and math in-struction also are negatively correlated with teacher re-sponsibility (p < .01), suggesting that these faculty mayfeel less responsible for the success of students thanother survey respondents who teach in the technologies.Further research may identify additional differences be-tween faculty members from the different STEM disci-plines or institutions but were beyond the scope of thisstudy.

QUANTITATIVE CONCLUSIONS

The findings from the quantitative data analysis inthis study provide valuable information about commu-nity college STEM instruction. The findings indicate thata variety of instructional practices are currently used tovarying degrees by STEM faculty. Findings also suggestthat inclusive beliefs combined with comfort with tech-nology and pedagogical competencies are positively as-sociated with the use of a range of instructional practices.Having time available for the development of inclusivepractices also is shown to be a critical factor, suggest-ing that when classroom discipline and administrative

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demands are minimized, faculty are more likely to de-velop new teaching methods.

In reviewing the effect of the belief scales across allnine instructional practices variables, patterns begin toemerge. As indicated by the beta scores in Tables 4 and5, the belief scales inclusive mindset, technology com-fort level, need for change — discipline, and pedagogicalcompetency are the three variables that are most predic-tive of a range of instructional practices.

The quantitative analysis has provided data that arevery useful in understanding current instructional prac-tices. In order to gain a more complete and in-depth un-derstanding, qualitative methods also were employed.The next section reports the results of the qualitativeanalysis.

QUALITATIVE RESULTS

Data from interviews, observations, and documentscollected were analyzed and sorted into categories andsubcategories. Anfara, Brown, and Mangione (2002) rec-ommend the use of tabular strategies for documentingthe relationship between data sources and categories inorder to strengthen credibility and provide the readerwith a visual representation of methodological rigor.The model used was adapted from the work of Con-stas (1992) and Brown (1999) and shows three levels ofanalysis. Level 1 depicts open coding. Level 2 depictsthe consolidation of those units into more manageableand workable units. Level 3 is the final iteration of cat-egory development. In Level 3, central categories thatbest addressed the research questions were developed.The process of categorization created three main areasfor further exploration: instructional methods and strate-gies, inclusion, and barriers. These areas were designatedas domains and broken down into categories and subcat-egories. A domain is an important basic unit upon whichfurther analysis is built. Taxonomical analysis developedby Spradley (1980) was then used to analyze the meaningand relationship among domains, categories, and sub-categories. Table 6 is taxonomy for the three domains.The number of respondents who reported a particularsubcategory is listed in parentheses.

Instructional Methods and Strategies

QUALITATIVE CONCLUSION

Overall results of interviews and classroom observa-tions suggest that participating STEM faculty appear touse a variety of instructional practices and strategies. Itappears that for the most part, instructors are aware ofdiversity and the need for inclusion and attempt to teachin ways that reach a diverse population of students. Nev-ertheless, findings related to use of materials and tech-

nologies in the classroom suggests that improvementis needed in the area of accessibility. Faculty reporteda number of barriers that prevent them and their col-leagues from developing and using more inclusive meth-ods. By far the greatest number of barriers listed by fac-ulty members are related to financial and institutionaldemands. Instructors indicated that high teaching loadsand lack of time to develop new methods are the greatestbarriers to inclusive pedagogy.

The findings suggest that reaching a diverse popula-tion is important to community college STEM faculty.However, the qualitative sample was small and mayhave consisted of only faculty members who were in-terested in the topic of inclusion; thus, it is impossible togeneralize findings to other community college faculty.

SUMMARY OF COMBINED QUANTITATIVEAND QUALITATIVE FINDINGS

What are the Current Teaching Methods?

Findings from this study revealed some significantresults that pertain to STEM instructional approaches incommunity colleges. Findings discussed in more detailbelow indicated that (a) community college instruction atthe studied institutions is different from that reported inprevious studies conducted primarily at four-year insti-tutions, (b) the use of a variety of instructional methodsis greater than expected, (c) many community collegeSTEM faculty recognize differences in learner types andattempt to design instruction to meet learner variation,and (d) a gap between knowledge of pedagogy and theactual application of instructional practices in the class-room exists.

Previous research highlighted the continued relianceon traditional lecture as the primary form of instructionused by full-time and part-time STEM faculty at four-year institutions (Kardash & Wallace, 2001; NCES, 2002;Seymour & Hewitt, 1997; Walczyk & Ramsey 2003). Com-munity college STEM faculty members in this study ap-pear to be very different than those at four-year institu-tions. Both quantitative and qualitative findings suggestthe use of multiple methods by these faculty members.Descriptive statistics showed a slight majority of facultymembers having reported using a variety of pedagog-ical methods and presentation strategies. Of those fac-ulty members, 30% of faculty members never use a tra-ditional lecture format, while 28% occasionally and 42%frequently use a lecture format. Although the lecture for-mat continues to be reported by faculty members as animportant method of instruction, it is often used in con-junction with other methods.

Although the need for improvement continues, thefindings suggest that more instructors in this study areusing varied instructional approaches than are using atraditional lecture format. Multiple regression analysis

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Table 6Taxonomy—Instructional methods and strategies

Domain Category Subcategories (n)

Instructional Methodsand Strategies

Traditional Methods Lecture (1)*Interactive Methods Group work (3)

Lecture-questions (5)Lecture-discussion (5)Student engagement and connection (6)Experiential learning (2)

Hands-on Methods Problem based learning (4), Participatory demonstration (4)Manipulatives (3), Visualizations (4) Projects (3), Portfolios (2)Student presentations (2)

Technological Methods Video/DVD (1), Slides (1), Online labs (1) Course managementsystems (4) Internet (2), PowerPoint (2) Discussion boards (3),E-mail (1) Computer Assisted Instruction (1) Video lectures (1),Calculators (2) Interactive computer problems (2) Coursematerial available electronically (4) Computer demonstrations(2)

Inclusion Beliefs Importance of learner type (8)* Adapting to instructor methods (1)Inclusive Practices Use of multimodal methods (5) Connection, interaction (9) Real

life examples (6)Methods of Accommodation Integrated with instruction (7) Separate from instruction (4)

Barriers Attitudinal Beliefs of science faculty (1) Culture of department (2) Studentresistance (1) Faculty resistance (1)

Physical Setting Equipment (2) Classroom design (1) Availability of instructionalmaterial (2)

Requirements Proliferation of information (1) Standards/learning outcomes (1)Administrative constructs (1)

Resources Professional development (4) Not knowing what to do (2) Lack ofexperience with diversity (3)

Finance Faculty pay (4) Lack of state Support (3)Institutional Demands Class size (2) Faculty teaching loads (7) Size of school (1)

Part-time instructors (1) Time (10)

∗ Indicates the number of faculty reporting the use of each method.

showed that personal characteristics do not appear toconstrain or enable instructors in the adoption of inclu-sive approaches; the one exception is full-time status,which is associated with knowledge of and adoption ofa variety of pedagogical methods. However, multiple re-gression analysis does show that some environmentalfactors do influence the adoption of these methods. Notsurprisingly, faculty members who report having time todevelop new teaching methods and who have reducedadministrative and discipline related demands are morelikely to use a variety of instructional methods. Also, anumber of beliefs (such as inclusive mindset, pedagogi-cal competency, and technology comfort level) are asso-ciated with the use of a variety of instructional practices.

As noted above, a review of the findings has shownthat the community college faculty in this study are dif-ferent in a number of ways from their colleagues in four-year institutions in that they are adopting a variety of dif-ferent practices in larger numbers than expected. A briefdiscussion of some of the factors associated with the waycommunity college STEM faculty members view theirstudents further clarifies this difference. The qualitative

findings revealed that these faculty members think aboutinclusion, the way students learn, and how to best reachthem. The majority of faculty members interviewed indi-cated that instruction should be modified to be inclusiveof students with disabilities and students who learn indifferent ways. The overall consensus was that teach-ing that promotes student engagement and incorporatesmultiple methods best serves all students. Of course, be-cause the instructors were voluntary participants theremay have been some bias and these findings should befollowed up in future research. Nevertheless, these re-sults are supported by quantitative data that showedinclusive beliefs to be held by many faculty membersand positively correlated with the adoption of multiplemethods of instruction. Descriptive statistics showed theadjusted mean for inclusive mindset to be 3.99 with 59%of faculty showing that they had a strong propensitytoward inclusive thinking. Multiple regression analysisshowed a positive association between inclusive mind-set and eight of the nine instructional practices and anegative association with the ninth practice, traditionalteaching. Within the inclusive mindset scale, over 78% of

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faculty members agreed that they would be receptive tomaking changes to accommodate students with disabil-ities. These findings are significant in that they highlightan awareness and willingness on the part of many com-munity college faculty members to adapt their teachingto the needs of their students. However, willingness doesnot necessarily translate to practice. Do instructors havethe necessary knowledge about pedagogy to be able toeffectively modify their instruction and the other factorsmight influence them? The majority of faculty in thisstudy indicated that they are knowledgeable about dif-ferent teaching approaches.

What are the Levels of Awareness RegardingTeaching Practices?

Awareness and knowledge of teaching practices arecentral to the use of a variety of instructional methodsby faculty. Findings from multiple regression analysisin this study showed that pedagogical competency orknowledge about different teaching was positively as-sociated with the use of a variety of pedagogical prac-tices, student engagement, and diversified instruction.The literature review indicated that most college facultymembers teach the way they were taught (Silver et al.,1998) and for the most part, do not have exposure to orknowledge of pedagogical techniques and diverse learn-ers (Sunal et al., 2001). The findings in this study werequite different. Over 79% of the faculty members in thisstudy indicate that they agree or strongly agree that theyare knowledgeable about different teaching practices. Anumber of them indicated that they know and use manyof the pedagogical practices listed in this study. In ad-dition, 58% reported teaching in ways that are differentfrom the way they were taught. The community collegeSTEM faculty members in this study appear to be moreknowledgeable about pedagogical practices than whatwas noted in literature about four-year faculty. However,it is important to note that significant numbers continueto teach in traditional ways, and the extent to which in-structional practices are used varies considerably amongfaculty members and among disciplines. For example,mathematics instructors reported an overall lower use oftechnology, multimedia, and varied presentation strate-gies, but they seemed more likely than science instructorsto use interactive learning. In addition, classroom obser-vations showed that even when inclusive practices werein place some technologies and materials remained in-accessible to individuals with disabilities. For instance,online labs could not be used with assistive technology,reducing accessibility for blind or low vision users. Ma-terials used in the classroom, such as small print graphsand charts and a video clip without captioning, wouldalso be inaccessible to some students with disabilities.Overall, the results suggest that the adoption of inclu-

sive pedagogy is complex and a number of factors comeinto play.

What are the Factors that Inhibit Faculty fromUsing Inclusive Practices?

An analysis of the quantitative results revealed thatboth beliefs and environmental factors are associatedwith the use of different pedagogical practices. Hav-ing an inclusive mindset clearly points to the use of thegreatest number of instructional practices, followed bytechnology comfort level and pedagogical competency.The absence of an inclusive mindset is associated withlower reported use and is a barrier to implementationof inclusive pedagogy. If faculty do not have an inclu-sive mindset they are much more likely to teach in tradi-tional ways. If faculty reported discomfort in the use oftechnology they were less likely to use varied teachingstrategies, technology in the classroom, or multimediainstruction. If faculty members reported that that theywere not knowledgeable about teaching approaches thenthey were also less likely to understand student learningneeds, to implement practices that engage students, orto be in tune with the needs of different learners.

Even when faculty members do possess these beliefs,other environmental influences may prevent the adop-tion of inclusive practices. Most notable among these fac-tors is time for instructional development. Time has beenreported as a barrier to the implementation of innovativeand inclusive practices in a number of the studies listedin the review of literature (Bianchini, Whitney, Brenton,& Hilton-Brown, 1999; Silver et al., 1998). The findingsfrom this study support the conclusion that time is a sig-nificant barrier. Time combined with the lack of institu-tional resources, such as financial support and profes-sional development, represent important barriers to thedevelopment of pedagogical knowledge and applicationof different teaching practices.

The findings from the qualitative portion of this studysupport the quantitative findings and provide furtherclarification. Administrative and discipline related de-mands as well as the high teaching loads of commu-nity college faculty members were the most frequentlycited barriers to inclusive pedagogy reported in facultyinterviews. Many of the faculty members reported thatit was difficult to keep up with current course loads andfelt that even though they might want to develop newmethods, time constraints prevented them from doingso. Instructors reported the lack of both institutional andsystem-wide support. On a systems level, lack of statefinancial support and low faculty pay scales were re-ported as barriers because they both impacted moraleand made obtaining necessary funding difficult. On aninstitutional level, faculty members reported inconsis-tent support and lack of funding as barriers. The levels

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of support and funding varied between institutions andbetween departments at the same institution. In addi-tion, lack of appropriate professional development op-portunities was seen as a deterrent in that professionaldevelopment is limited and often not geared to the spe-cific needs of faculty.

IMPLICATIONS FOR PRACTICE ANDRESEARCH

Implications for Practice

This study sheds new light on the extent to whichbelief, knowledge, and environmental factors convergewith each other in the process of community collegeSTEM instruction. The study shows that these factorsare important and that they all contribute to the likeli-hood that a faculty member will use multimodal teach-ing methods. The findings from this study indicate that,within these three institutions, there is a strong inclu-sive mindset and a desire to teach in a way that reachesall students, suggesting a potential for the continueddevelopment of inclusive strategies. The identificationof barriers and obstacles that impede the developmentof more inclusive teaching methods provides insightinto possible new directions and solutions to improvepractice.

This study has shown that in order to effectively de-velop new instructional approaches, practitioners needan inclusive belief system, knowledge of pedagogy, fa-miliarity with new techniques and technologies, time,and resources. How does the community college con-tinue to foster these beliefs and create an environmentwhere inclusive pedagogy can thrive? The findings fromthis study point to a number of specific activities thatwould be helpful to faculty: (a) provide information ondiversity, disability, accessibility, and learning styles tomake faculty aware of the nature of the student bodyand their learning needs; (b) provide opportunities forfaculty to learn more about instructional methods; (c)create opportunities for faculty to become more familiarand comfortable with the use of technology in the class-room; (d) establish policies that give faculty the time andresources needed to develop new instructional methods;and (e) create awards and incentives for faculty who dodevelop multimodal teaching methods.

In order for these activities to be successful, they mustbe provided in a way that respects the needs and timedemands faculty currently face. For example, offeringgeneric professional development opportunities duringpeak teaching hours or busy times during the semestermay not be helpful to faculty. A more useful approachmight be to provide educational opportunities based onneeds assessments from individual departments and tooffer at them at convenient times for faculty. Once newtechniques are learned, faculty must be provided with

the time and resources needed to fully develop them.The priorities and policies that institutions set aroundtime and resources are critical to the implementation ofnew instructional practices.

Implications for Further Research

The topic of inclusive pedagogy in post-secondarySTEM education has not been well researched. This studyis one step in closing the research gap and findings sug-gest the need for continued research in this area. There areseveral important directions this research should take.First, this study focused on instructional practices as theypertain to a broad group of learners with differences anddisabilities. The next step would be to determine whetherany differences based on the type of disability exist. Forexample, do faculty think about and respond differentlyto students with different types of disabilities? Does in-struction change for students with learning disabilitiesas opposed to students who may be blind or mobilityimpaired? These are important distinctions that warrantfuture investigation.

Through the use of factor analysis this study identifiedclusters of related data that specifically relate to instruc-tional practices, knowledge of pedagogical approaches,and beliefs about teaching and learning. The clusters rep-resent dimensions of practice that could provide a baseupon which future research in STEM instruction couldbe built. For example, the three dimensional scales couldbe used in the development of a target profile for lev-els of inclusive pedagogy. Faculty members could thenbe assessed against this profile to determine areas whereimprovement is needed. The profile could also form thebase for evaluation criteria at the institutional level.

This study established that a relationship exists be-tween beliefs, knowledge, and environmental factorsand instructional practice. The extent of those relation-ships bears further investigation. For example, howmuch knowledge is needed in order for an instructorto begin to implement new practices and what types ofknowledge prove most useful? At what point do beliefsbecome critical in the process of developing new instruc-tional strategies and are there specific ways to encouragemore inclusion? More research is needed to better under-stand the complex interplay between and among thesefactors.

The relationship between inclusive pedagogy andlearning outcomes must be investigated. The research re-viewed in this study showed that students in general dolearn best in environments where learner-centered andnontraditional teaching occurs. However, no researchcurrently exists that looks at the relationship betweenlearning outcomes for students with disabilities and in-clusive teaching methods within post-secondary educa-tion. Although, we can speculate that a relationship doesexist, empirical evidence is needed.

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Future research should include a component that eval-uates community college administrators’views about in-clusive teaching. The actions of administrators are criti-cal to any institutional systemic change and their viewsabout inclusion may influence the success of any pro-gram. Further research is needed to clarify their be-liefs and attitudes about investing in inclusive teachingpractices.

This study was conducted at three community col-leges in the northeastern United States. The results arenot generalizable to other two-year institutions or tofour-year colleges. Expanded research involving a largernumber of institutions is needed in order to gain a morecomplete picture of postsecondary STEM instruction.

CONCLUSION

The primary purpose of this study was to investigatecommunity college STEM instruction in order to increaseknowledge about inclusive pedagogy and to provide rec-ommendations for improved pedagogy. Previous studiesof postsecondary STEM instruction largely ignored two-year colleges and did not include a focus on disability.An examination of community college STEM instructionhas provided new insights and has pointed to differencesamong two-year and four-year STEM instructors.

Findings revealed that a significant number of thesecommunity college faculty members have an inclusivemindset and believe in adapting their instruction toaccommodate learner differences. These faculty mem-bers also appear more knowledgeable about pedagog-ical practices than what has been reported in previousliterature about four-year faculty. Many of the facultymembers are using multimodal instructional methods.However, a significant gap still exists between what theybelieve and know and what is actually put into instruc-tional practice. A number of barriers that prohibit the useand development of inclusive practices were identified inthis study; most significant among the barriers reportedwere the lack of an inclusive mindset, lack of knowledgeabout pedagogy, high teaching loads, and lack of timefor instructional development.

The findings from this study are merely a first stepin explaining the complex relationship among beliefs,knowledge, environment, and instruction. Hopefully thefindings from this study will stimulate further thoughtand investigation about inclusive pedagogy and the crit-ical role it plays in STEM instruction for students withdisabilities.

NOTES

1. Results of factor analysis for each dimension and alphareliabilities for scale items are available by contacting the au-thor.

2. In factor analysis Varimax rotation is an orthogonal rota-tion used to extract factors so that the factor axes are maintained

at right angles. Each factor will tend to have either large or smallloadings of any particular variable, thus leading to results thatmake it possible to identify each variable with a single factor.

3. A table of correlation coefficients for all variables is avail-able by contacting the author.

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Mary Moriarty has served as principal investigator and Di-rector on several federal projects that relate to universal designand inclusive pedagogy. She is currently coordinating the as-sessment of Enrollment Management and Academic SupportServices at Springfield Technical Community College as wellas serving as the college’s ADA Coordinator. Her research in-terests include the evaluation of STEM instruction, inclusivepedagogy, and disability in higher education.

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Inclusive Pedagogy: Teaching Methodologies to Reach Diverse Learners in Science Instruction