Flipped classroom use in chemistry education: results from a survey of postsecondary faculty members

Shalini Srinivasan a, Rebecca E. Gibbons a, Kristen L. Murphy b and Jeffrey Raker *ac
aDepartment of Chemistry, University of South Florida, 4202 East Fowler Ave., CHE 205, Tampa, Florida 33620, USA. E-mail: jraker@usf.edu
bDepartment of Chemistry and Biochemistry, University of Wisconsin-Milwaukee, 3210 N. Cramer St., Milwaukee, Wisconsin 53211, USA
cCenter for the Improvement of Teaching and Research on Undergraduate STEM Education, University of South Florida, 4202 East Fowler Ave., CHE 205, Tampa, Florida 33620, USA

Received 2nd April 2018 , Accepted 12th July 2018

First published on 25th July 2018


Abstract

The aim of this study is to offer a current snapshot of flipped classroom use in postsecondary chemistry education. Data from a national survey of chemistry faculty members in the United States formed the basis of an investigation into the instructional contexts in which flipped classroom pedagogies are employed in postsecondary chemistry education. Our results reveal an association between flipped classroom use and the level at which a course is taught; in addition, our results provide support for the utility of flipped classrooms as a means for incorporation of pedagogical practices focused on active and collaborative learning.


Introduction

The flipped classroom is an approach in which content and skills typically taught during class time are delivered outside the classroom, freeing up classroom time for active learning including case studies, discussions, experiments, labs, or simulations (Hamdan et al., 2013; See and Conry, 2014; Scheg, 2015). While the idea of a flipped classroom is invariably associated with the use of videos for content delivery, the concept has evolved to encompass a broader array of learning activities such as reading assignments (e.g., O’Flaherty and Phillips, 2015) and other direct instruction delivery method such as audio (e.g. podcasts or voice-recorded lectures) or pre-solved problems (e.g., Bergmann and Sams, 2012; See and Conry, 2014). The origins of the flipped classroom pedagogy are muddled: Walvoord and Anderson (1998) first mentioned the flipped-class method as a way to make information available to students online prior to the class and utilize classroom time to allow students to apply this information. Around the same time, economics professors implemented an “inverted classroom” in response to diverse student and faculty perceptions of instruction; in doing so, Lage, Platt and Treglia (2000) found that students preferred the “inverted classroom” model to a traditional classroom. Prior to the class, students viewed video recordings in which case studies and simulation games were employed to describe economic principles (Lage et al., 2000). Much of the work reported on flipped classrooms credits their introduction and design to two high school teachers, Bergmann and Sams (2012), who prepared and posted their lecture videos online to assist students who had missed class or needed extra help.

Instances of flipped classroom use occur in all areas of the academy (e.g., humanities, education, physical sciences; Lage et al., 2000; Kim et al., 2014; Hurtubise et al., 2015; Moran and Milsom, 2015; Wanner and Palmer, 2015; Schwartz et al., 2016; Swart and Wuensch, 2016). Empirical research on the effectiveness of flipped classrooms is based on quasi-experimental comparisons with lecture-based classrooms models (Winquist and Carlson, 2014; Gundlach et al., 2015; Peterson, 2016; McNally et al., 2017), pre-post measures of learning (Sarawagi, 2014; McNally et al., 2017), or examining student perceptions and satisfaction with the course (Lage et al., 2000; Carlson and Winquist, 2011; Strayer, 2012; Critz and Knight, 2013; McLaughlin et al., 2013; Wilson, 2013; Bristol, 2014; Butt, 2014; See and Conry, 2014; McNally et al., 2017; Rucker et al., 2017). While a survey research study documenting use of flipped classrooms has been conducted in postsecondary education (Watts et al., 2015), the current study offers a discipline-specific profile of faculty who utilize flipped classrooms, a key level of analysis missing from academy-level investigations of flipped-classroom use.

Active learning strategies and use of evidence based instructional practices

Evidence-based instructional practices (EBIPs) are characterized as practices based on empirical and theoretical understandings of teaching and learning (Ambrose et al., 2010; Groccia and Buskit, 2011; Kober, 2015; Missett and Foster, 2015). EBIPs can be employed as strategies, to increase active learning, within existing course structures, e.g. think-pair-share (Lyman, 1987; King, 1993), or act as systems that facilitate the design of entire courses: e.g. problem-based learning (Barrows, 1980), peer-led team learning (Gosser and Roth, 1998; Gosser et al., 2001), and process oriented guided inquiry learning (Farrell et al., 1999). Despite variations in the level of evidence to support these practices and contention over definitions that are often entwined, the development and dissemination of these practices involves an intention effort to demonstrate effectiveness (cf., Hempenstall, 1999; Prince, 2004; Gambrill, 2006; Michael, 2006; Naccarato and Karakok, 2015; Slavin, 2017).

The incorporation of active learning strategies into postsecondary education is a broad goal of national and international STEM organizations and professional societies. The transformation of teaching and learning practices in postsecondary STEM education is an ongoing narrative among those invested in the development and sustained utilization of reform initiatives (National Research Council, 1999; Rothman and Narum, 1999; National Research Council, 2003; Kuenzi, 2008; National Research Council, 2011; National Research Council, 2012; Jidesjö et al., 2015; McDonald, 2016; Fendos, 2018). The inefficacy of passive lecture models on student understanding and retention is well documented (cf., Halloun, 1985; Seymour and Hewitt, 1997; Freeman et al., 2014). A gradual shift from teacher-centered pedagogies to more student-centered learning environments has necessitated flexibility in how the learning process is conceptualized and how understanding of what is being done in the classroom setting is captured (see Means, 1994; Hannafin et al., 1997; Organization for Economic Cooperation and Development, 2006; Kearney et al., 2007; Johnson et al., 2012; Kim et al., 2014; Wanner and Palmer, 2015). Literature on teaching and learning suggests that regardless of discipline, student engagement in active and collaborative instructional environments leads to improved student learning outcomes (see Kuh et al., 2005, 2007; Pascarella and Terenzini, 2005).

Although investigations of the adaptation of such pedagogies typically dwindle when development and dissemination monies cease (National Science Foundation, 1996; Center for Science, 1999; Fairweather, 2008; Austin, 2008), there has been an emergence of survey research studies across several discipline-based educational research fields; these studies attempt to make claims about the prevalence of EBIPs, with the intent of making measurements across time to better understand adoption practices in STEM education (e.g., Macdonald et al., 2005; Handelsman et al., 2006; Henderson and Dancy, 2009; Borrego et al., 2010).

Flipped classroom pedagogies in chemistry

In the chemistry context, use reports include implementations at K-12 (Bergmann and Sams, 2012; Delgado et al., 2015; Hao and Lee, 2016; Lo and Hew, 2017) and postsecondary levels (Smith, 2013; Christiansen, 2014; Yeung and O’Malley, 2014; Butzler, 2015; Fautch, 2015; Fitzgerald and Li, 2015; Flynn, 2015; Muzyka, 2015; O’Flaherty and Phillips, 2015; Rein and Brookes, 2015; Rossi, 2015; Seery, 2015a, 2015b; Trogden, 2015; Weaver and Sturtevant, 2015; Yestrebsky, 2015; Eichler and Peeples, 2016; Hibbard et al., 2016; Lenczweksi, 2016; Mooring et al., 2016; Reid, 2016; Robert et al., 2016; Ryan and Reid, 2016; Shattuck, 2016; Christiansen et al., 2017a, 2017b; Rau et al., 2017; Liu et al., 2018). What has not been clearly delineated is how class time that would have been spent on content and skill instruction is used. For courses such as general chemistry, the delineation of time to enact an active learning module is inhibited by increasing class sizes, including the variation in level of preparedness of incoming students based on the size and type of institution (e.g., Eichstadt, 1993; Michael, 2007; Deri et al., 2017). In response, Robert et al. (2016) implemented a hybrid of flipped classroom pedagogies and peer-led team learning for use in large class sizes. Our study offers clarity as to what instructional practices are paired with flipped classroom use in postsecondary chemistry education.

The growing number of research publications on the topic point to increased use of flipped classrooms in postsecondary chemistry education. Research suggests a myriad of chemistry content and affective learning gains resulting from use of flipped classroom pedagogies. The activities students are asked to do outside the classroom (including what the students actually complete before attending class) and how the now freed class time is used, are important covariates to the effectiveness of flipped classrooms. Despite tangential evidence for increased use of flipped classroom pedagogies, there has been no measure of how pervasive flipped classroom pedagogies are in postsecondary chemistry education; in addition, we have little understanding of the contexts (e.g., gateway chemistry courses or large-enrollment courses) in which flipped classroom pedagogies are more prevalently used. Data from a national survey of postsecondary chemistry faculty in the United States, analyzed using weighted-data analytic techniques to account for sampling error and nonresponse bias, are used to describe flipped classroom use in postsecondary chemistry education.

Background

Theoretical framework

Our study is situated in the Teacher-Centered Systemic Reform (TCSR) model (see Fig. 1; Woodbury and Gess-Newsome, 2002). Developed from studies of undergraduate reform efforts, this model offers applicability in the context of this work as we consider adoption of an instructional practice within a complex educational system. Enacted practices used by a faculty member (or ‘teacher’ as characterized in the TCSR model) are interdependent on the teachers’ thinking (i.e., beliefs about teaching and learning), personal context (e.g., participation in professional development on teaching and learning, or applying and receiving grant monies to reform courses or curricula), and cultural context (e.g., number of students enrolled in a course, perceived institutional barriers to reform efforts, or disciplinary expectations about how courses should be taught). These contextual levels warrant consideration individually or collectively when addressing change efforts (Woodbury and Gess-Newsome, 2002).
image file: c8rp00094h-f1.tif
Fig. 1 Teacher-centered systemic reform model (Woodbury and Gess-Newsome, 2002; Gess-Newsome et al., 2003).

Although frameworks such as Rogers’ Technology Adoption Life Cycle (TALC; 2003) and the four-part model proposed by Henderson et al. (2011) have been used to investigate adoption of student-centered instructional practices (Towns, 2010; Emenike and Holme, 2012; Gibbons et al., 2017), there are certain limitations to each model; for instance, TALC is limited in its ability to make broad claims about how a new innovation is adopted, as it does not take into account the social and organizational contexts that influence adoptive practices (MacVaugh and Schiavone, 2010; Cua, 2012). While the four-part model overcomes this limitation by being more inclusive of classroom and instructional contexts when analyzing EBIP adoption, it does not account for faculty teaching beliefs when creating new methods.

In contrast to both frameworks, the TCSR model offers a broad encompassing perspective of how and why faculty members choose to enact instructional practices in their courses. Stains et al. (2015) utilized the TCSR model when evaluating a workshop for new chemistry faculty. Personal factors such as teaching experience and training, contextual factors such as classroom, department, and institutional influences, and lastly, teachers’ beliefs, self-efficacy and dissatisfaction with current teaching practices were outcomes targeted for evaluation when faculty participated in the workshop. The TCSR framework has also been utilized in previous evaluations of instructional techniques by postsecondary chemistry faculty members (Gibbons et al., 2018).

Thus, we employ aspects of personal and contextual factors in the TCSR model to provide a lens for our survey from which to understand current enacted practices e.g., flipped classroom pedagogies in this study.

Research question

For our study, we use a national survey of faculty members framed by the TCSR model to provide a contextual snapshot of flipped classroom use in postsecondary chemistry education. Additionally, we explore instructional practices utilized in combination with flipped classroom pedagogies. This question guides our study:

• In what contexts are U.S. postsecondary faculty members utilizing flipped classroom pedagogies as a component of their courses?

Methodology

Assessment of enacted practices and contextual factors

A survey of chemistry faculty members was conducted via Qualtrics (in February 2017) on enacted instructional and assessment practices in an undergraduate non-laboratory course that the respondent felt they had the most control over and influence on in the last three years. The University of South Florida's Institutional Review Board approved the study (no. Pro00025183).

Data for this study were collected as part of a larger survey that included items about classroom practices and pedagogical techniques used in the respondent's chosen course, respondent demographics, departmental and institutional contexts, and respondent's beliefs about teaching and learning.

The study reported herein is focused on faculty members’ responses to how frequently they utilized flipped classroom pedagogies in their course. In addition, we evaluate six hypothesized factors, at the personal and contextual levels of the TCSR model, that have been shown to be linked in other contexts to faculty members’ choices to enact particular instructional practices:

Perceived faculty control. Respondents indicated the degree of control they exert over various aspects of their selected course. Implementation of active learning pedagogical practices is more likely among faculty who believe they have a greater perceived locus of control over course attributes and subsequent course planning (cf., Perry and Dickens, 1987; Perry et al., 1997; Perry, 2003; Michael, 2007; Linville et al., 2011; Chiasson et al., 2015).

Total course enrollment. Respondents provided the total enrollment for the last offering of their selected course. Number of students enrolled has been shown to be associated with EBIP adoption (e.g., Michael, 2007; Cash et al., 2017; Gibbons et al., 2017; Shadle et al., 2017).

Course level. Respondents selected levels for which their selected course was primarily offered: first year (or freshman), second year (or sophomore), third year (or junior), fourth year (or senior). Decisions surrounding the implementation of a new curriculum or pedagogy are influenced by factors innate to the course level (e.g., Metzger, 2015; Mack and Towns, 2016; Gibbons et al., 2017).

Institutional control. Public or private institutional control is a proxy for a number of factors including institution size and faculty-to-student ratios (e.g., DeHaan, 2005; Shadle et al., 2017). Institutional characteristics such as size and type are shown to impact faculty teaching practices and institutional cultures (e.g., Cox et al., 2011). Institutional control data was imputed into our data set from the Integrated Postsecondary Education Data System (IPEDS; U.S. Department of Education, 2016).

Highest chemistry degree awarded. This metric is used as a proxy for the degree of teaching versus research foci of the institution; institutions with graduate degree offerings are assumed to have a greater focus on research (Cox et al., 2011). Data were imputed into our data set from IPEDS.

Faculty rank. Tenure status has been shown to have a direct association with degree of EBIP adoption (e.g., Landrum et al., 2017; Shadle et al., 2017). In addition, departmental characteristics such as promotion or tenure policies have been reported to have an influence on awareness and adoption of instructional practices (e.g., Lund and Stains, 2015).

Participants and data collection

IPEDS data were analyzed to identify institutions that had awarded one or more bachelors degrees in chemistry in the five years prior to the study. This resulted in a total of 1137 institutions (see Table 1). A comprehensive list of postsecondary chemistry faculty was compiled using publicly available online faculty lists of email addresses. Faculty members from two-year institutions were not included in this study; difficulties with inconsistent listings of chemistry programs (either unlisted or under a different college such as natural sciences) and a rapid turnover of faculty (abundance of part-time and adjunct faculty) resulted in an unclear definition of a population of study from which to sample faculty.
Table 1 Strata, sample definition, respondents, and response rates
Stratum Inst. control Highest chem. deg. awarded # of inst. # of faculty Sample W i # of resp. URR (%) W f
Note: Inst. = institution(s), Chem. = chemistry, Deg. = degree, # = number, Wi = initial weight, Resp. = respondents, URR = unit response rate, Wf = final weight.
1 Public Bachelors 241 2828 1231 2.30 203 16.5 13.9
2 Public Graduate 223 6059 2263 2.68 260 11.5 23.3
3 Private Bachelors 569 4221 1084 3.89 216 19.9 19.5
4 Private Graduate 81 1880 1810 1.04 150 8.30 12.5
Totals 1114 14[thin space (1/6-em)]988 6388 829 14.4


Faculty lists were unavailable for 23 institutions, resulting in a list of 14[thin space (1/6-em)]998 total faculty at 1114 total institutions. A stratified random sampling method (Neyman, 1934) was used to select 6388 faculty from four strata defined by institutional control (i.e., public or private) and highest chemistry degree awarded (i.e., bachelors and graduate; see Table 1). The desired number of responses for each stratum was based on a 95% confidence level and 5% confidence interval (Rao, 1968) and projected response rates based on a 2016 iteration of the same survey. Initial weights (Wi) for each stratum were determined as the inverse of the probability of selection. A total of 829 faculty members responded to the survey, resulting in a unit response rate of 14.4%. On account of the low unit response rate, as defined in the National Center for Education Statistics (2002), final weights (Wf) are utilized in analyses to address potential sampling error and nonresponse bias.

Statistical analyses

Final weights, stratification, and a finite population correction were used in Stata 14 (StataCorp, 2015) to conduct statistical analyses. Upper- and lower-bound 95% confidence intervals (CIs) are reported for measures where appropriate. Weighted survey data analyses are used, including two-way cross-tabulations with tests of independence followed by weighted logistic regressions (and associated odds ratios) as unstandardized effect size measures (Chen et al., 2010; Lalongo, 2016), and weighted means analyses of variance (ANOVAs) followed by η2 (eta-squared) effect size measures (Cohen, 1988).

Results and discussion

Descriptive statistics are presented for the overall use of flipped classrooms followed by descriptive, inferential statistics, and effect sizes that address flipped classroom use based on the six hypothesized contextual factors. Faculty participants responded to the survey items in reference to a single undergraduate non-laboratory course taught in the last three years as chosen by themselves; consequently, we use [course] throughout this paper to show where the title (as provided by the respondent) of the course was inserted into the survey item.

Overall adoption of flipped classrooms

Respondents were asked to indicate the frequency with which they used flipped classroom in their course. The following definition of a flipped classroom was provided for respondents: “Primary content delivery mode occurs outside of the classroom (i.e. using videos, textbook, activities) and the application of content occurs inside the classroom.” Responses are condensed into two categories – “Use” and “Nonuse” (see Table 2). The “Use” category includes respondents who selected “Every class meeting,” “Weekly,” and “Several times per semester.” Confidence intervals at the 95% level, based on sampling weights, are reported.
Table 2 Weighted frequencies of flipped classroom use
Response option Total (%) 95% CI
Lower bound Upper bound
Every class meeting 6.8 5.2 8.8
Weekly 6.1 4.6 8.1
Several times per semester 12.4 10.3 14.8
Rarely 13.4 11.2 15.9
Never 61.4 57.9 64.7
“Use” 25.2 22.3 28.4
“Nonuse” 74.8 71.6 77.7


Our results are similar to numbers found from a broader study of all disciplines in the academy: 29% of faculty members have adopted flipped classroom pedagogies (Watts et al., 2015); and, 17% of faculty members report having tried the pedagogy.

Perceived control over classroom space and pedagogical decisions

Respondents were asked to rate how much control they had over several aspects of their course including classroom space and pedagogical decisions; each item was rated on a scale from zero to ten with a zero indicating “no control” and a ten indicating “complete control”. Weighted means and weighted-means ANOVAs are used to evaluate differences between control measures by flipped classroom use and non-use (see Table 3).
Table 3 Perceived control over classroom space and pedagogical decisions by use of flipped classroom pedagogies
Item Use Non-use ANOVA
Mean lb ub Mean lb ub df,df F p η 2
Methods used to teach the course (e.g., small group work, problem-based learning) 9.2 9.0 9.5 9.3 9.2 9.5 1,817 0.32 0.570 0.0039
Class space used (e.g., lecture hall, moveable tables and chairs, computer lab) 4.5 4.0 5.0 4.3 4.0 4.6 1,687 0.19 0.661 0.0003
Content and topics covered (e.g., chapters covered in the textbook) 7.3 6.9 7.7 7.5 7.3 7.7 1,791 0.69 0.407 0.0009
Maximum number of students who can enroll in the course 4.2 3.7 4.8 4.7 4.4 5.1 1,633 2.14 0.144 0.0034


Given that respondents were asked to answer the item based on a course for which they had the most control over, high control over “methods” is expected and adds validity to our survey responses. At the same time, lower ratings for items regarding “class space used” and “maximum student enrolment in the course” are expected as these decisions are most likely administratively decided and based on available space/classroom configurations.

These results also reveal a lack of statistical difference between faculty use and non-use of flipped classrooms regardless of their degree of perceived control over classroom space and pedagogical decisions. While Shadle et al. (2017) have reported loss of autonomy over content and methods as a faculty-identified barrier for STEM education change, the results in Table 4 indicate that factors beyond personal autonomy over classroom space and pedagogical decisions potentially influence decisions to use flipped classroom pedagogies.

Table 4 Flipped classroom use by course and institutional demographics
Item Choice Use Non-use ANOVA
% lb ub % lb ub df,df F p η 2
Note: Chem. = chemistry, Deg. = degree, Bach. = bachelors, Grad. = graduate.
Size Small 24.4 20.5 28.8 75.6 71.2 79.5 1,823 0.33 0.568 0.0004
Large 26.2 22.0 30.8 73.9 69.2 78.1
Level Lower 27.9 24.0 32.1 72.1 67.9 76.0 1,823 4.44 0.035 0.0056
Upper 21.2 17.0 26.1 78.8 73.9 83.0
Institutional control Private 22.9 18.7 27.6 77.2 72.4 81.3 1,823 1.68 0.200 0.0020
Public 26.9 23.0 31.2 73.1 68.8 77.1
Highest chem. deg. awarded Bach. 26.3 22.3 30.8 73.7 69.2 77.7 1,823 0.43 0.510 0.0005
Grad. 24.3 20.2 28.9 75.7 71.1 79.8


Course and institution contexts

Course. Respondents were asked to indicate the total number of students enrolled in all sections of their course (total course enrolment); course enrolment was divided into binary categories: “large” course sizes were characterized as those with enrolments greater than the median course size (i.e., 80 students) while enrolments lower than the median size were categorized as “small” course sizes. We acknowledge that a binary distribution of course enrolment might not extend to all institutions, requiring further delineation of course sizes based on institution size and type; however, given that much of the debate in higher education on class size and resulting impact on educational practice and policy employs a binary categorization of “large” or “small” class size, our study utilizes a similar classification (Feld and Grofman, 1977). There was no observed significant difference between use/non-use and class size (see Table 4).

Respondents were asked to indicate at what levels their course was taught: first year (or freshman), second year (or sophomore), third year (or junior), fourth year (or senior). First and second year course levels were condensed into a “lower” level course, while third and fourth year course levels were combined and characterized as an “upper” level course.

When characterized by course level, a statistically significant difference emerges between users and non-users of the flipped classroom pedagogy. A weighted logistic regression yields the following: Faculty teaching lower level courses are 1.44 times (p < 0.05) more likely to use flipped classrooms than faculty teaching upper level courses. This finding is supported by a report that roughly 75% of flipped courses are in general and organic chemistry, with the remainder in analytical, biochemistry, general-organic-biological (GOB) and analytical chemistry (Muzyka and Luker, 2016).

Institution. Use of flipped classroom pedagogies is evaluated for associations with institutional control (i.e., public or private) and highest chemistry awarded (i.e., bachelors or graduate) at the institution. Two-way cross tabulations with tests of independence are used to characterize data associated with course and institutional demographics (see Table 4). There are no significant differences between users and non-users of flipped classrooms based on institutional attributes (e.g., public versus private control and highest chemistry degree awarded).

These course and institution results are in contrast to those observed in the use of classroom response systems (CRSs), with CRS use in a distinct niche in large, lower level courses at public institutions (Gibbons et al., 2017). In the case of flipped classrooms, course level is the only attribute that had an independent contribution to the difference between users and non-users; furthermore, the lack of a statistically significant difference with regard to course size suggests that the choice to use flipped classrooms might not be entirely utility-oriented as in the case of CRSs (Gibbons et al., 2017). From a curricular perspective, integration of videos that are provided as ancillary materials with textbooks and the presence of well-structured and effective open-access resources are more common for content in lower level courses, consequently potentially leading to increased use of flipped classrooms in these courses (cf., Storer, 2016).

Faculty rank

The test of independence for faculty rank (tenure status) by use of flipped classroom pedagogies is significant and has a small effect size, F(3.00,2468.72) = 3.5213, p = 0.0145, η2 = 0.0112. Respondents were asked to indicate their tenure status at the time they were responding to the survey. Two-way cross tabulations with tests of independence are used to characterize these data (see Table 5).
Table 5 Faculty rank (tenure status) by use of flipped classroom pedagogies
Item Use Non-use
% lb ub % lb ub
Tenured 21.9 18.5 25.8 78.1 74.2 81.5
On tenure track, but not tenured 26.5 19.6 34.8 73.5 65.2 80.4
Not on tenure track, but my institution has a tenure system 35.2 27.8 43.4 64.8 56.6 72.2
No tenure system at my institution 26.3 12.3 47.5 73.7 52.5 87.7


Although faculty rank has been reported to have an impact on the extent of awareness and adoption of instructional practices (Landrum et al., 2017), our results (see Table 5) do not reveal a significant association between flipped classroom use and rank. Landrum et al. (2017) utilized a survey to measure the instructional climate at their institution and noted that tenured/tenure-track faculty scored significantly lower than non-tenure-track faculty in terms of institutional support provided for teaching; furthermore, contrary to the perceptions of teaching/research balance held by their non-tenure-track counterparts, tenured/tenure-track faculty believed that teaching was undervalued relative to research. Despite these perceptions, tenure/tenure-track faculty in the Landrum et al. (2017) study reported significantly higher scores on the EBIP adoption scale. In the context of chemistry, Landrum et al. (2017) noted the diversity in scores on the EBIP adoption scale and suggested that adoption of EBIPs in chemistry might necessitate the use of multiple strategies. Lund and Stains (2015) reported that less than 50% of chemists indicated their teaching being impacted by departmental reward systems, despite roughly 50% of chemists noting both departmental promotion and pressures related to tenure as influential factors. Thus, while faculty rank does not reveal an independent, significant association with flipped classroom use in our study, it merits consideration within the broader scope of departmental and institutional support structures, which may collectively drive or hinder the use of instructional practices.

Instructional context

Bergmann and Sams (2012) noted that the flipped classroom pedagogy is not in competition with instructional strategies such as PLTL and POGIL; instead it is a medium that exploits the potential of active learning by providing content lectures outside classroom, thereby releasing class time for incorporation of other instructional practices (e.g., with peer-led team learning; Robert et al., 2016). Exploration of which practices were used in combination with flipped classroom pedagogies was addressed by asking respondents to indicate how frequently they used a series of instructional practices in their [course]. Associations between use/nonuse of flipped classrooms and use/nonuse of instructional practices are reported in Table 6.
Table 6 Association between use/non-use of flipped classrooms and use/non-use of other instructional practices in the classroom
Instructional practice “Use” Flipped classroom F(df,df)b Odds ratiosc
Users versus non-usersa
a U = users; NU = non-users. b p-values are p < 0.001 for all F-statistics. c Odds ratios = measures of unstandardized effect sizes in instances of statistically significant χ2 results; only significant odds ratios are reported (p < 0.001).
Lecturing U = 92.2 [87.6, 95.2] F(1,821) = 39.9 Non-users 15.6× more likely
NU = 99.5 [98.6, 99.8]
Assigning students to work in groups U = 83.7 [77.9, 88.2] F(1,821) = 36.2 Users 3.3× more likely
NU = 60.5 [56.6, 64.4]
Moving through the class, guiding ongoing student work U = 88.7 [83.5, 92.4] F(1,823) = 49.1 Users 4.8× more likely
NU = 62.2 [58.2, 66.0]
Extended discussion with small groups or individuals U = 68.4 [61.6, 74.5] F(1,823) = 24.4 Users 2.3× more likely
NU = 48.0 [44.0, 52.1]
Initiating a whole class discussion, including explanation, opinion, or judgment provided by students. U = 63.0 [56.0, 69.5] F(1,822) = 15.2 Users 1.9× more likely
NU = 46.8 [42.8, 50.9]
Think-Pair-Share (TPS): Posing a problem or question, having students work on it individually for a short time and then forming pairs and reconciling their solutions, followed by a whole classroom discussion of students’ responses U = 49.4 [42.4, 56.4] F(1,820) = 11.5 Users 1.8× more likely
NU = 35.7 [32.0, 39.7]
Just-in-Time-Teaching (JiTT): Asking students to individually complete homework assignments a few hours before class, reading through their answers before class and adjusting the lessons accordingly U = 35.0 [28.7, 42.0] F(1,820) = 53.5 Users 4.0× more likely
NU = 12.0 [9.6, 14.9]
Peer-Led Team Learning (PLTL): In groups, students complete a worksheet with problems designed to build conceptual understanding and problem-solving skills. Small groups are led by peer leaders (i.e., trained undergraduate students that have taken the course) U = 34.6 [28.3, 41.5] F(1,822) = 12.3 Users 1.9× more likely
NU = 22.1 [19.0, 25.6]
Teaching with case studies: Asking students to analyze case studies of historical or hypothetical situations that involve solving problems or making decisions. U = 31.0 [25.0, 37.8] F(1,821) = 10.9 Users 1.8× more likely
NU = 19.7 [16.7, 23.2]
Process Oriented Guided Inquiry (POGIL): In groups, students complete a worksheet designed around the learning cycle. U = 38.0 [31.5, 45.0] F(1,820) = 30.7 Users 2.7× more likely
NU = 18.8 [15.9, 22.1]
Problem-based Learning (PBL): Acting primarily as a facilitator and placing students in self-directed teams to solve open-ended problems that require significant learning of new course material. U = 42.1 [35.4, 49.2] F(1,823) = 39.6 Users 3.0× more likely
NU = 19.7 [16.7, 23.1]


Based on results in Table 6, faculty who do not utilize flipped classrooms as a pedagogy are ∼16 times more likely to use lecturing as an instructional practice. As the implementation of flipped classrooms requires the restructuring of a classroom to move a direct instructional practice such as lecture out of the classroom (cf., Talbert, 2017) this finding is expected; furthermore, it also provides an added measure of validity to the survey responses. Given that practices such as group work and moving through class form the core of most in-class active learning strategies, it is not surprising that faculty members who utilize flipped classrooms are more likely to report use of these engaging practices.

As a strategy, flipped classrooms are unique in that there is no clearly defined model that describes what it takes to operationalize the strategy (Mazur, 1996; Novak et al., 1999; Gosser et al., 2001; Marrs et al., 2003; Hanson, 2006). Schwartz et al. (2016) noted that a potential barrier to adopting a flipped classroom pedagogy is the misconception that a one-size-fits-all approach exists for its implementation. Despite the prevalence of YouTube and publisher created videos, the use and adaptation of flipped classroom pedagogies is still time intensive. Chemistry faculty who have successfully employed flipped classrooms echo this sentiment: Flynn (2015) and Yestrebsky (2015) cite video preparation, planning and organization of structured in- and out-of-class activities as time consuming efforts when converting to a flipped classroom. Flynn (2015) utilized a variety of tools (e.g., electronic whiteboard, document camera, CRS, iPad) in addition to activities such as think-pair-share and predict–observe–explain; the author credits successful flipped classroom implementation in various course levels and sizes to teaching assistants, prior experience in similar classroom formats, students’ enthusiasm, institutional and technical support from the teaching and learning support service. While the use of these tools and technical support may not be ubiquitous, Holton and Rink (2016) recommend in-class time be spent on any activities and experiences that will help students learn. With regards to video preparation, Hagen (2016) notes that while the first year of implementation is time consuming, it is a one-time investment. Preparation time in subsequent years for a flipped classroom with team-based learning is no more than a traditional lecture course.

Based on our results, roughly 25% of chemistry faculty members in postsecondary education implemented the flipped classroom approach in the course for which they have the most control. When examined across disciplines, the percentage of faculty who have adopted flipped classrooms is 29% (Watts et al., 2015). Studies from Lund and Stains (2015); Borrego, Froyd, and Hall (2010); and Henderson and Dancy (2009) highlight the philosophical, technical, and logistical factors that need to be addressed for the adoption of new instructional practices. While clearly defined guidelines exist for in-class strategies and practices for flipped classrooms, faculty are still exploring the most effective in-class practices for their classrooms; furthermore, there is a shortage of reports that detail the integration of these strategies during the in-class component of the flipped classroom pedagogy. Emergence of design principles for use of flipped classrooms support use of the pedagogy as a tool that frees class time to increase more student-centered active learning strategies and practices (cf., Kim et al., 2014; Muzyka and Luker, 2016; Lo and Hew, 2017; Reidsema et al., 2017).

Limitations

Two limitations should be considered in light of the results and discussion we have offered about our survey data: first, the survey study in which the data used in this paper were collected had broad goals to characterize the instructional and assessment practices in postsecondary chemistry courses. This minimized our ability to ask targeted “how” and “why” questions of our respondents when they reported using flipped-classroom pedagogies in the course for which they had the most control. Therefore, we are only able to speculate on why there are no observed statistical significant differences between flipped-classroom use and some course and institution contexts; note, differences have been previously observed between instructional practice use and the course and institution contexts we evaluated (e.g., Michael, 2007; Cash et al., 2017; Gibbons et al., 2017; Shadle et al., 2017). Additionally, we speculate that flipped-classroom use provides a means for the incorporation of more active learning strategies during main classroom time; while presented as unidirectional, we recognize that flipped classrooms allow for active learning, and a decision to use active learning may lead to a choice to use flipped classrooms in courses where content coverage is a priority. A series of follow-up survey items or an interview study would allow for a more in-depth understanding of the results presented. While our report cannot be discounted for the surface level characterization of flipped-classroom use, we highly encourage more large-scale, broadly generalizable studies to explore how and why faculty members choose to implement flipped-classroom pedagogies.

Second, the survey population was limited to chemistry faculty members in the United States. Therefore, the estimation that one in four chemistry faculty members choose to regularly use some form of flipped-classroom pedagogies in the course for which they have the most control should be cautiously generalized to contexts outside of the United States. We recognize that resource availability and cultural influences, among other factors, greatly influence the choices faculty make; note, these factors constitute key pathways of the TCSR model (Woodbury and Gess-Newsome, 2002; Gess-Newsome et al., 2003) that framed our survey and results. Based on our reading of the literature, we do, however, argue that our results regarding the association between flipped-classroom use and other active learning instructional practices is generalizable, as our empirical results support many of the anecdotal and hypothesized claims made by educators worldwide regarding why flipped-classroom pedagogies are implemented in postsecondary chemistry courses (cf., Abeysekera and Dawson, 2015; Flynn, 2015; O’Flaherty and Phillips, 2015; Seery, 2015a, 2015b; Muzyka and Luker, 2016). Much of the survey research work done in chemical education research is situated in the United States; we recommend that the study reported herein (and other survey work that has been conducted from a U.S.-centric perspective) be done in other countries where suitable faculty member populations can be defined and sampled. Such work would allow for a global-level comparison and international cultural analysis of the dissemination and implementation of active learning strategies.

Conclusion

We investigated the class, institution, and instructional contexts in which flipped classroom pedagogies are utilized by postsecondary chemistry faculty members in the U.S. We estimate that 25% of chemistry faculty members utilize flipped classrooms in the course for which they have the most control. Regardless of the degree of perceived control faculty possessed over aspects of the course they taught, there were no significant difference between users and non-users of flipped classrooms. While non-significant differences are reported for flipped classroom use based on several course and institution context measures, significant differences were only observed between users and non-users of flipped classrooms based on course level; this finding is potentially attributed to the increased open-access publication of videos as supporting material for textbooks at lower levels of chemistry, thereby providing a component that could be used as out-of-class material for use of the flipped classroom pedagogy. Our data also reveal that faculty use of flipped classrooms is significantly associated with use of active learning strategies and instructional practices. These results support the idea that the flipped classroom pedagogy is not in competition with these strategies, but rather acts as a framework that allows and supports their integration into the instructional context.

Conflicts of interest

This material is based upon support from the ACS Examinations Institute and the University of South Florida. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the ACS Examinations Institute or the University of South Florida. Jeffrey R. Raker is the Associate Director of the ACS Examinations Institute; the University of South Florida's Institutional Review Board has reviewed this study and deemed that Dr Raker's role with the ACS Examinations Institute is not likely to affect the safety of study participants or the scientific quality of the study. Kristen L. Murphy is the Director of the ACS Examinations Institute.

References

  1. Abeysekera L. and Dawson P., (2015), Motivation and cognitive load in the flipped classroom: definition, rationale and a call for research, High. Educ. Res. Dev., 34, 1–14.
  2. Ambrose S. A., Bridges M. W., Lovett M. C., DiPietro M. and Norman M. K., (2010), How learning works: seven research-based principles for smart teaching, San Francisco, CA: Jossey-Bass.
  3. Austin A. E., (2008), Promoting evidence-based change in undergraduate science education, http://sites.nationalacademies.org/cs/groups/dbassesite/documents/webpage/dbasse_072578.pdf, accessed February 22, 2018.
  4. Barrows H. S., (1980), Problem-based learning: an approach to medical education, New York: Springer.
  5. Bergmann J. and Sams A., (2012), Flip your classroom: reach every student in every class every day, Washington, DC: International Society for Technology in Education.
  6. Borrego M., Froyd J. E. and Hall T. S., (2010), Diffusion of engineering education innovations: a survey of awareness and adoption rates in US engineering departments, J. Eng. Educ., 99, 185–207.
  7. Bristol T. J., (2014), Flipping the classroom, Teach. Learn. Nurs., 9, 43–46.
  8. Butt A., (2014), Student views on the use of a flipped classroom approach: evidence from Australia, Bus. Educ. Accred., 6, 33–43.
  9. Butzler K. B., (2015), ConfChem conference on flipped classroom: flipping at an open-enrollment college, J. Chem. Educ., 92, 1574–1576.
  10. Carlson K. A. and Winquist J. R., (2011), Evaluating an active learning approach to teaching introductory statistics: a classroom workbook approach, J. Stat. Educ., 19, 1–23.
  11. Cash C. B., Letargo J., Graether S. P. and Jacobs S. R., (2017), An analysis of the perceptions and resources of large university classes, CBE-Life Sci. Educ., 16, 1–12.
  12. Center for Science M. and Engineering Education, Committee on Undergraduate Science Education, (1999), Transforming undergraduate education in science, mathematics, engineering, and technology, Washington, DC: National Academy Press.
  13. Chen H., Cohen P. and Chen S., (2010), How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies, Commun. Stat. Simul. Comput., 39, 860–864.
  14. Chiasson K., Terras K. and Smart K., (2015), Faculty perceptions of moving a face-to-face course to online instruction, J. Coll. Teach. Learn., 12, 231–240.
  15. Christiansen M. A., (2014), Inverted teaching: applying a new pedagogy to a university organic chemistry class, J. Chem. Educ., 91, 1417–1425.
  16. Christiansen M. A., Lambert A. M., Nadelson L. S., Dupree K. M. and Kingsford T. A., (2017a), In-class versus at-home quizzes: Which is better? A flipped learning study in a two-site synchronously broadcast organic chemistry course, J. Chem. Educ., 94, 157–163.
  17. Christiansen M. A., Nadelson L., Etchberger L., Cuch M., Kingsford T. A. and Woodward L. O., (2017b), Flipped learning in synchronously-delivered, geographically-dispersed general chemistry classrooms, J. Chem. Educ., 94, 662–667.
  18. Cohen J., (1988), Statistical Power Analysis for the Behavioral Sciences, Hillsdale, NJ: Lawrence Earlbaum.
  19. Cox B. E., McIntosh K. L., Reason R. D. and Terenzini P. T., (2011), A culture of teaching: policy, perception, and practice in higher education, Res. High. Educ., 52, 808–829.
  20. Critz C. M. and Knight D., (2013), Using the flipped classroom in graduate nursing education, Nurse Educ., 38, 201–213.
  21. Cua F. C., (2012), The good, the bad, and the missing of the “diffusion of innovations” theory: a commentary essay, Int. J. Inf. Syst. Soc. Change, 3, 64–80.
  22. DeHaan R. L., (2005), The impending revolution in undergraduate science education, J. Sci. Educ. Technol., 14, 253–269.
  23. Delgado A. J., Wardlow L., McKnight K. and O’Malley K., (2015), Educational technology: a review of the integration, resources, and effectiveness of technology in K-12 classrooms, J. Inf. Technol. Educ. Res., 14, 397–416.
  24. Deri M. A., McGregor D. and Mills P., (2017), in Christiansen M. A. and Weber J. M. (ed.), Teaching and the Internet: The Application of Web Apps, Networking, and Online Tech for Chemistry Education, American Chemical Society, vol. 1270, pp. 75–97.
  25. Eichler J. F. and Peeples J., (2016), Flipped classroom modules for large enrollment general chemistry courses: a low barrier approach to increase active learning and improve student grades, Chem. Educ. Res. Pract., 17, 197–208.
  26. Eichstadt K. A., (1993), A large lecture hall activity-writing your name “in chemistry”, J. Chem. Educ., 70, 37.
  27. Emenike M. E. and Holme T. A., (2012), Classroom response systems have not “crossed the chasm”: Estimating numbers of chemistry faculty who use clickers, J. Chem. Educ., 89, 465–469.
  28. Fairweather J. S., (2008), Linking evidence and promising practices in science, technology, engineering, and mathematics (STEM) undergraduate education: a status report for the national academies national research council board on science education, http://www.nsf.gov/attachments/117803/public/Xc--Linking_Evidence--Fairweather.pdf, accessed February 22, 2018.
  29. Farrell J. J., Moog R. S. and Spencer J. N., (1999), A guided-inquiry general chemistry course, J. Chem. Educ., 76, 570–574.
  30. Fautch J. M., (2015), The flipped classroom for teaching organic chemistry in small classes: is it effective? Chem. Educ. Res. Pract., 16, 179–186.
  31. Feld S. L. and Grofman B., (1977), Variation in class size, the class size paradox, and some consequences for students, Res. High. Educ., 6, 215–222.
  32. Fendos J., (2018), U.S. experiences with STEM education reform and implications for Asia, Int. J. Comp. Educ. Dev., 20, 51–66.
  33. Fitzgerald N. and Li L., (2015), Using presentation software to flip and undergraduate analytical chemistry course, J. Chem. Educ., 92, 1559–1563.
  34. Flynn A. B., (2015), Structure and evaluation of flipped chemistry courses: organic & spectroscopy, large and small, first to third year, English and French, Chem. Educ. Res. Pract., 16, 198–211.
  35. Freeman S., Eddy S. L., McDonough M., Smith M. K., Okoroafor N., Jordt H. and Wenderoth M. P., (2014), Active learning increases student performance in science, engineering, and mathematics, Proc. Natl. Acad. Sci. U. S. A., 111, 8410–8415.
  36. Gambrill E., (2006), Evidence-based practice and policy: choice ahead, Res. Soc. Work Pract., 16, 338–357.
  37. Gess-Newsome J., Southerland S. A., Johnston A. and Woodbury S., (2003), Educational reform, personal practical theories, and dissatisfaction: the anatomy of change in college science teaching, Am. Educ. Res. J., 40, 731–767.
  38. Gibbons R. E., Laga E. E., Leon J., Villafañe S. M., Stains M., Murphy K. and Raker J. R., (2017), Chasm crossed? Clicker use in postsecondary chemistry education, J. Chem. Educ., 94, 549–557.
  39. Gibbons R. E., Villafañe S. M., Stains M., Murphy K. L. and Raker J. R., (2018), Beliefs about teaching and enacted instructional practices: An investigation in postsecondary chemistry education, J. Res. Sci. Teach.,  DOI:10.1002/tea.21444.
  40. Gosser D. K. and Roth V., (1998), The workshop chemistry project: peer-led team learning, J. Chem. Educ., 75, 185–187.
  41. Gosser D. K., Cracolice M., Kampmeier J. A., Roth V., Strozak V. S. and Varma-Nelson P., (2001), Peer-led Team Learning: A Guidebook, New Jersey: Prentice Hall.
  42. Groccia J. E. and Buskit W., (2011), Need for evidence-based teaching, New Dir. Teach. Learn., 128, 5–11.
  43. Gundlach E., Richards K. A. R., Nelson D. and Levesque-Bristol C., (2015), A comparison of student attitudes, statistical reasoning, performance and perceptions for web-augmented traditional, fully online, and flipped sections of a statistical literacy class, J. Stat. Educ., 1.
  44. Hagen J. P., (2016), in Muzyka B. and Luker C. S. (ed.), The Flipped Classroom Volume 1: Background and Challenges, American Chemical Society, vol. 1223, pp. 55–72.
  45. Halloun I. A., (1985), The initial knowledge state of college physics students, Am. J. Phys., 53, 1043–1048.
  46. Hamdan N., McKnight P., McKnight K. and Arfstrom K. M., (2013), The Flipped Learning Model: A White Paper based on the Literature Review titled: A Review of Flipped Learning, New York: Flipped Learning Network.
  47. Handelsman J., Miller S. and Pfund C., (2006), Scientific teaching, USA: WH Freeman & Company.
  48. Hannafin M., Hill J. and Land S., (1997), Student-centered learning and interactive multimedia: status, issues, and implications, Contemp. Educ., 68, 94–99.
  49. Hanson D. M., (2006), Instructor's Guide to Process-oriented Guided Inquiry Learning, Lisle, IL: Pacific Crest.
  50. Hao Y. W. and Lee K. S., (2016), Teaching in flipped classrooms: exploring pre-service teachers’ concerns, Comput. Hum. Behav., 57, 250–260.
  51. Hempenstall K., (1999), The gulf between educational research and policy: the example of direct instruction and whole language, Effect. Sch. Pract., 18, 15–29.
  52. Henderson C. and Dancy M. H., (2009), Impact of physics education research on the teaching of introductory quantitative physics in the United States, Phys. Rev. ST Phys. Educ. Res., 5, 020107.
  53. Henderson C., Beach A. and Finkelstein N., (2011), Facilitating change in undergraduate STEM instructional practices: An analytic review of the literature, J. Res. Sci. Teach., 48, 952–984.
  54. Hibbard L., Shannon S. and Wells B., (2016), Examining the effectiveness of a semi-paced flipped learning format in a college general chemistry sequence, J. Chem. Educ., 93, 24–30.
  55. Holton A. J. and Rink R. D., (2016), in Muzyka B. and Luker C. S. (ed.), The Flipped Classroom Volume 1: Background and Challenges, American Chemical Society, vol. 1223, pp. 123–134.
  56. Hurtubise L., Hall E., Sheridan L. and Han H., (2015), The flipped classroom in medical education: engaging students to build competency, J. Med. Educ. Curric. Dev., 2, 35–43.
  57. Jidesjö A., Danielsson A. and Björn A., (2015), Interest and recruitment in science: a reform, gender and experience perspective, Proc. – Soc. Behav. Sci., 167, 211–214.
  58. Johnson L., Adams S. and Cummins M., (2012), Technology outlook for Australian tertiary education 2012–2017: an NMC horizon report regional analysis, Austin, TX: The New Media Consortium.
  59. Kearney K., Nicholas H., Mahar S. and Herrick C., (2007), Personalizing education: from research to policy and practice, Melbourne, Australia: Office for Educational Policy and Innovation, Department of Education and Early Childhood Development.
  60. Kim M. K., Kim S. M., Khera O. and Getman J., (2014), The experience of flipped classrooms in an urban university: an exploration of design principles, Internet High. Educ., 22, 37–50.
  61. King A., (1993), From sage on the stage to guide on the side, Coll. Teach., 41, 30–35.
  62. Kober N., (2015), Reaching Students: What Research says about Effective Instruction in Undergraduate Science and Engineering, Washington, DC: National Academy Press.
  63. Kuenzi J. J., (2008), Science, technology, engineering, and mathematics (STEM) education: Background, federal policy, and legislative action, http://digitalcommons.unl.edu/crsdocs, accessed February 25, 2018.
  64. Kuh G., Kinzie J., Schuh J. and Witt E., (2005), Student Success in College: Creating Conditions that Matter, Washington, DC: Association for the Study of Higher Education.
  65. Kuh G., Kinzie J., Buckley J., Bridges B. and Kayek J., (2007), Piecing together the Student Success Puzzle: Research, Propositions, and Recommendations, Washington, DC: Association for the Study of Higher Education.
  66. Lage M. J., Platt G. J. and Treglia M., (2000), Inverting the classroom: a gateway to creating an inclusive learning environment, J. Econ. Educ., 31, 30–43.
  67. Lalongo C., (2016), Understanding the effect size and its measures, Biochem. Med., 26, 150–163.
  68. Landrum R. E., Viskupic K., Shadle S. E. and Bullock D., (2017), Assessing the STEM landscape: the current instructional climate survey and the evidence-based instructional practices adoption scale, Int. J. STEM Educ., 4, 25.
  69. Lenczweksi M. S., (2016), Scaffolded semi-flipped general chemistry designed to support rural students' learning, J. Chem. Educ., 93, 1999–2003.
  70. Linville J. E., Antony J. S. and Hayden R. A., (2011), Unionization and perceived control among community college faculty, Community College Journal of Research and Practice, 35, 330–351.
  71. Liu Y., Raker J. R. and Lewis J. E., (2018), Evaluating student motivation in organic chemistry courses: moving from a lecture-based to a flipped approach with peer-led team learning, Chem. Educ. Res. Pract., 19, 251–264.
  72. Lo C. K. and Hew K. F., (2017), A critical review of flipped classroom challenges in K-12 education: possible solutions and recommendations for future use, Res. Pract. Technol. Enhanced Learn., 12, 1–22.
  73. Lund T. J. and Stains M., (2015), The importance of context: an exploration of factors influencing the adoption of student-centered teaching among chemistry, biology, and physics faculty, Int. J. STEM Educ., 2, 1–21.
  74. Lyman F., (1987), Think-pair-share: an expanding teaching technique, MAA-CIE Cooperative News, 1, 1–2.
  75. Macdonald R. H., Manduca C. A., Mogk D. W. and Tewksbury B. J., (2005), Teaching methods in undergraduate geoscience courses: results of the 2004 on the cutting-edge survey of US faculty, J. Geosci. Educ., 53, 237.
  76. Mack M. R. and Towns M. H., (2016), Faculty beliefs about the purposes for teaching undergraduate physical chemistry courses, Chem. Educ. Res. Pract., 17, 80–99.
  77. MacVaugh J. and Schiavone F., (2010), Limits to the diffusion of innovation: a literature review and integrative model, Eur. J. Innov. Manage., 13, 197–221.
  78. Marrs K. A., Blake R. E. and Gavrin A. D., (2003), Web-based warm up exercises in just-in-time teaching, J. Coll. Sci. Teach., 33, 42–47.
  79. Mazur E., (1996), Peer Instruction: A User's Manual, New Jersey: Prentice Hall.
  80. McDonald C. V., (2016), STEM education: a review of the contribution of the disciplines of science, technology, engineering and mathematics, Sci. Educ. Int., 27, 530–569.
  81. McLaughlin J. E., Griffin L. M., Esserman D. A., Davidson C. A., Glatt D. M., Roth M. T. and Mumper R. J., (2013), Pharmacy student engagement, performance, and perception in a flipped satellite classroom, Am. J. Pharm. Educ., 77, 196.
  82. McNally B., Chipperfield J., Dorsett P., Del Fabbro L., Frommolt V., Goetz S., Lewohl J. M., Molineux M., Pearson A. G., Reddan G., Roiko A. and Rung A., (2017), Flipped classroom experiences: student preferences and flip strategy in a higher education context, High. Educ., 73, 281–298.
  83. Means B., (1994), in Means B. (ed.), Technology and Education Reform: The Reality behind the Promise, San Francisco: Jossey-Bass.
  84. Metzger K. J., (2015), Collaborative teaching practices in undergraduate active learning classrooms: a report of faculty team teaching models and student reflections from two biology courses, Bioscene, 41, 3–9.
  85. Michael J., (2006), Where's the evidence that active learning works? Adv. Physiol. Educ., 30, 159–167.
  86. Michael J., (2007), Faculty perceptions about barriers to active learning, Coll. Teach., 55, 42–47.
  87. Missett T. C. and Foster L. H., (2015), Searching for evidence-based practice: a survey of empirical studies on curricular interventions measuring and reporting fidelity of implementation published during 2004–2013, J. Adv. Acad., 26, 96–111.
  88. Mooring S., Mitchell C. E. and Burrows N. L., (2016), Evaluation of a flipped, large-enrollment organic chemistry course on student attitude and achievement, J. Chem. Educ., 93, 1972–1983.
  89. Moran K. and Milsom A., (2015), The flipped classroom in counselor education, Counselor Education and Supervision, 54, 32–43.
  90. Muzyka J. L., (2015), ConfChem conference on flipped classroom: just-in-time teaching in chemistry courses with moodle, J. Chem. Educ., 92, 1580–1581.
  91. Muzyka J. L. and Luker C. S., (2016), in Muzyka J. L. and Luker C. S. (ed.), The Flipped Classroom Volume 1: Background and Challenges, American Chemical Society, vol. 1223, p. 1.
  92. Naccarato E. and Karakok G., (2015), Expectations and implementations of the flipped classroom model in undergraduate mathematics courses, Int. J. Math. Educ. Sci. Technol., 46, 968–978.
  93. National Center for Education Statistics, (2002), NCES Statistical Standards, Washington, DC: US Department of Education.
  94. National Research Council, (1999), Transforming Undergraduate Education in Science, Mathematics, Engineering, and Technology, Washington, DC: National Academies Press.
  95. National Research Council, (2003), Improving Undergraduate Instruction in Science, Technology, Engineering, and Mathematics: Report of a Workshop, Washington, DC: National Academies Press.
  96. National Research Council, (2011), Successful K-12 STEM Education: Identifying Effective Approaches in Science, Technology, Engineering, and Mathematics, Washington, DC: National Academies Press.
  97. National Research Council, (2012), A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas, Washington, DC: National Academies Press.
  98. National Science Foundation, (1996), Shaping the future: new expectations for undergraduate education in science, mathematics, engineering, and technology, Washington, DC: National Science Foundation.
  99. Neyman J., (1934), On the two different aspects of the representative methods: the method of stratified sampling and the method of purposive selection, J. R. Stat. Soc., Ser. A, 97, 558–606.
  100. Novak G., Patterson E. T., Gavrin A. D. and Christian W., (1999), Just-in-time teaching: blending active learning with web technology, Upper Saddle River, NJ: Prentice Hall.
  101. O’Flaherty J. and Phillips C., (2015), The use of flipped classrooms in higher education: a scoping review, Internet and High. Educ., 25, 85–95.
  102. Organization for Economic Cooperation and Development, (2006), Schooling for Tomorrow: Personalizing Education, Paris, France: OECD.
  103. Pascarella E. and Terenzini P., (2005), How College Affects Students: A Third Decade of Research, San Francisco: Jossey-Bass.
  104. Perry R. P., (2003), Perceived (academic) control and causal thinking in achievement settings, Can. Psychol., 44, 312–331.
  105. Perry R. P. and Dickens W. J., (1987), Perceived control and instruction in the college classroom: some implications for student achievement, Res. High. Educ., 27, 291–310.
  106. Perry R. P., Menec V. H., Struthers C. W., Hechter F. J., Schönwetter D. J. and Menges R. J., (1997), Faculty in transition: a longitudinal analysis of the role of perceived control and type of institutions in adjustment to postsecondary institutions, Res. High. Educ., 38, 519–556.
  107. Peterson D. J., (2016), The flipped classroom improves student achievement and course satisfaction in a statistics course: a quasi-experimental study, Teach. Psychol., 43, 10–15.
  108. Prince M., (2004), Does active learning work? A review of the research, J. Eng. Educ., 93, 223–231.
  109. Rao T. J., (1968), On the allocation of sample size in stratified sampling, Ann. Inst. Stat. Math., 20, 159–166.
  110. Rau M. A., Kennedy K., Oxtoby L., Bollom M. and Moore J. W., (2017), Unpacking “active learning”: a combination of flipped classroom and collaboration support is more effective but collaboration support alone is not, J. Chem. Educ., 94, 1406–1414.
  111. Reid S. A., (2016), A flipped classroom redesign in general chemistry, Chem. Educ. Res. Pract., 17, 914–922.
  112. Reidsema C., Kavanagh L., Hadgraft R. and Smith N., (2017), The Flipped Classroom: Practice and Practices in Higher Education, Singapore: Springer.
  113. Rein K. S. and Brookes D. T., (2015), Student response to a partial inversion of an organic chemistry course for non-chemistry majors, J. Chem. Educ., 92, 797–802.
  114. Robert J., Lewis S. E., Oueini R. and Mapugay A., (2016), Coordinated implementation and evaluation of flipped classes and peer-led team learning in general chemistry, J. Chem. Educ., 93, 1993–1998.
  115. Rogers E. M., (2003), Diffusion of Innovation, New York: Free Press.
  116. Rossi R. D., (2015), ConfChem conference on flipped classroom: improving student engagement in organic chemistry using the inverted classroom model, J. Chem. Educ., 92, 1577–1579.
  117. Rothman F. G. and Narum J. L., (1999), Then, now and in the next decade: a commentary on strengthening undergraduate science, mathematics, engineering and technology education, Washington, DC: Project Kaleidoscope.
  118. Rucker S. Y., Ozdogan Z. and Achkar M. A., (2017), Flipped classroom model for learning evidence-based medicine, Adv. Med. Educ. Pract., 8, 619–625.
  119. Ryan M. D. and Reid S. A., (2016), Impact of the flipped classroom on student performance and retention: a parallel controlled study in general chemistry, J. Chem. Educ., 93, 13–23.
  120. Sarawagi N., (2014), A flipped CS0 classroom: applying bloom's taxonomy to algorithmic thinking, J. Comput. Sci. Coll., 29, 21–28.
  121. Scheg A. G., (2015), Advances in Educational Technologies and Instructional Design: Implementation and Critical Assessment of the Flipped Classroom ExperienceIGI Global.
  122. Schwartz T. A., Andridge R. R., Sainani K. L., Stangle D. K. and Neely M. L., (2016), Diverse perspectives on a flipped biostatistics classroom, J. Stat. Educ., 24, 74–84.
  123. See S. and Conry J. M., (2014), Flip my class! A faculty development demonstration of a flipped classroom, Curr. Pharm. Teach. Learn., 6, 585–588.
  124. Seery M. K., (2015a), ConfChem conference on flipped classroom: student engagement with flipped chemistry lectures, J. Chem. Educ., 92, 1566–1567.
  125. Seery M. K., (2015b), Flipped learning in higher education chemistry: emerging trends and potential directions, Chem. Educ. Res. Pract., 16, 758–768.
  126. Seymour E. and Hewitt N. M., (1997), Talking About Leaving: Why Undergraduates Leave the Sciences, Boudler, CO: Westview Press.
  127. Shadle S. E., Marker A. and Earl B., (2017), Faculty drivers and barriers: laying the groundwork for undergraduate STEM education reform in academic departments, Int. J. STEM Educ., 4, 1–13.
  128. Shattuck J. C., (2016), A parallel controlled study of the effectiveness of a partially flipped organic chemistry course on student performance, perceptions, and course completion, J. Chem. Educ., 93, 1984–1992.
  129. Slavin R. E., (2017), Evidence-based reform in education, J. Educ. Stud. Placed Risk, 22, 178–184.
  130. Smith J. D., (2013), Student attitudes toward flipping the general chemistry classroom, Chem. Educ. Res. Pract., 14, 607–614.
  131. Stains M., Pilarz M. and Chakraverty D., (2015), Short and long-term impacts of the Cottrell Scholars collaborative new faculty workshop, J. Chem. Educ., 92, 1466–1476.
  132. StataCorp, (2015), Stata Statistical Software (Version 14), College Station, TX: StataCorp LP.
  133. Storer D. A., (2016), in Muzyka B. and Luker C. S. (ed.), The Flipped Classroom Volume 1: Background and Challenges, American Chemical Society, vol. 1223, pp. 17–27.
  134. Strayer J. F., (2012), How learning in an inverted classroom influences cooperation, innovation and task orientation, Learn. Environ. Res., 15, 171–193.
  135. Swart W. and Wuensch K. L., (2016), Flipping quantitative classes: a triple win, Decis. Sci.: J. Innov. Educ., 14, 67–89.
  136. Talbert R., (2017), Flipped Learning: A Guide for Higher Education Faculty, Sterling, VA: Stylus Publishing.
  137. Towns M. H., (2010), Crossing the chasm with classroom response systems, J. Chem. Educ., 87, 1317–1319.
  138. Trogden B. G., (2015), ConfChem conference on flipped classroom: reclaiming face time – how an organic chemistry flipped classroom provided access to increased guided engagement, J. Chem. Educ., 92, 1570–1571.
  139. U.S. Department of Education, (2016), Integrated Postsecondary Education Data System, Washington, DC: National Center for Education Statistics.
  140. Walvoord B. E. and Anderson V. J., (1998), Effective Grading: A Tool for Learning and Assessment, San Francisco: Jossey-Bass.
  141. Wanner T. and Palmer E., (2015), Personalizing learning: exploring student and teacher perceptions about flexible learning and assessment in a flipped university course, Comput. Educ., 88, 354–369.
  142. Watts J., Econmou K. and McGoldrick B., (2015), U.S. postsecondary faculty in 2015, Technical Report for FTI Consulting, Baltimore, MD.
  143. Weaver G. C. and Sturtevant H. G., (2015), Design, implementation, and evaluation of a flipped format general chemistry course, J. Chem. Educ., 92, 1437–1448.
  144. Wilson S., (2013), The flipped class: a method to address the challenges of an undergraduate statistics course, Teach. Psychol., 40, 193–199.
  145. Winquist J. R. and Carlson K., (2014), Flipped statistics class results: better performance than lecture over one year later, J. Stat. Educ., 22, 1–10.
  146. Woodbury S. and Gess-Newsome J., (2002), Overcoming the paradox of change without difference: a model of change in the arena of fundamental school reform, Educ. Policy, 16, 763–782.
  147. Yestrebsky C. L., (2015), Flipping the classroom in a large chemistry class – research university environment, Proc. – Soc. Behav. Sci., 191, 1113–1118.
  148. Yeung K. and O’Malley P. J., (2014), Making ‘the flip’ work: barriers to and implementation strategies for introducing flipped teaching methods into traditional higher education courses, New Dir. Inst. Res., 10, 59–63.

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