Mental models research to inform community outreach for a campus recycling program

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1467-6370.htm IJSHE 12,4 Mental models research to inform community outreach for a campus recycling program 322 Received 10 August 2010 Revised February 2011 Accepted 25 February 2011 Lauren Olson Office of Campus Sustainability, Michigan State University, East Lansing, Michigan, USA Joseph Arvai Haskayne School of Business, and The Institute for Sustainable Energy, Environment, and Economy, University of Calgary, Calgary, Canada and Decision Research, Eugene, Oregon, USA, and Laurie Thorp Residential Initiative on the Study of the Environment (RISE), Michigan State University, East Lansing, Michigan, USA Abstract Purpose – The purpose of this paper is to develop a better understanding of the state of knowledge of students and faculty on the Michigan State University (MSU) campus; identify relevant gaps in knowledge and misconceptions about recycling; and provide recommendations regarding how these gaps and misconceptions may be addressed through education and outreach Design/methodology/approach – Using mental models analysis, the current state of knowledge possessed by students and faculty was compared with a comprehensive inventory of on-campus recycling procedures and opportunities Findings – By combining data from individual mental models elicited from students and faculty members, an overall mental model that depicted the frequency with which subjects understood MSU-specific recycling concepts was developed This composite model, and the accompanying statistical analysis, revealed important gaps – on part of both students and faculty – in understanding for several key recycling concepts that are relevant to established campus-based waste reduction practices Originality/value – The mental models approach, which to the authors’ knowledge has yet to be applied to campus sustainability initiatives, provides program managers and outreach specialists with a constructive and transparent opportunity to develop and deploy program information that builds on existing knowledge while also meeting the new information needs of key stakeholders Keywords United States of America, Universities, Mental models, Recycling, Sustainability, Communication Paper type Research paper International Journal of Sustainability in Higher Education Vol 12 No 4, 2011 pp 322-337 q Emerald Group Publishing Limited 1467-6370 DOI 10.1108/14676371111168250 The authors wish to acknowledge the following individuals for their assistance with this research: Roger Cargill, Ruth Daoust, Kathy Lindahl, Terry Link, Fred Poston, Aimee Wilson, John Kerr, and Michael Kaplowitz This research was supported by Michigan State University’s Office of the Vice President for Finance and Operations Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and not necessarily reflect the views of the sponsor 1 Introduction One of the most common approaches to increasing community recycling rates is to encourage consumers, through education and outreach efforts, to improve their recycling habits with the hope that they will divert more recyclable materials (like paper products) from the waste stream to recycling collection University and college campuses have been particularly noteworthy players in discussions about increasing community recycling rates Each day college campuses are responsible for creating massive quantities of waste that, to a large extent, could be captured in a well-functioning recycling program Many everyday campus activities produce waste; these include the widespread use of white and colored paper, magazines, softbound books, cardboard, containers and utensils used by food services, plastic used in laboratories, used batteries, outdated electronic equipment; the list goes on and on Clearly, colleges and universities are motivated to recycle simply because they must dispose of waste products; and, in today’s budgetary climate, many colleges and universities see opportunities to generate revenue through the sale of recyclables An equally important motivator of campus recycling programs is the leadership role that colleges and universities play in society Most, if not all universities and colleges take pride in being at the forefront of the sustainability movement (Pike et al., 2003) and recycling programs provide good evidence of – and a good opportunities for public relations around – sustainability practices At Michigan State University (MSU), for example, the scope and scale of the campus recycling program has been expanding quickly Considering just paper products (white paper, mixed paper, newsprint, cardboard, etc.), recovery rates have increased eightfold from 200 metric tons collected in 1990 to 1,600 metric tons collected in 2008 A similar trend has been observed for glass, as well as No PETE (clear) and No PETE (colored and cloudy) plastic containers Despite widespread growth however, MSU’s current diversion rate (materials recycled instead of being sent to landfill) is considered to be relatively low by its own standards at 14 per cent As a result, MSU is currently in the process of expanding its campus-wide recycling (including reuse and composting) programs even further by increasing the number of local collection points and by opening a new, on-campus collection and sorting center At the same time, MSU is in the process of expanding the range of materials that may be routinely recycled on campus, with the target of a 30 per cent reduction the amount of solid waste generated by 2015 As a result of these changes, there is a need to a better job of informing and educating the campus community about both the importance of MSU’s expanded recycling program and how they can play a role in helping to implement it These needs motivated the research reported here The initial stage of collection – when the consumer is presented with the choice to recycle or not – is generally thought of as the most important stage of a recycling program because consumers are seen as the main driver of efficiency and efficacy in a recycling system (e.g in terms of correctly identifying and sorting recyclable materials, knowing about drop-off or collection points, etc.) Because a recycling program’s success is highly dependent on the consumer’s involvement, programs designed to increase engagement in recycling activities warrant study to inform people about: of the benefits of recycling; what is recyclable in the community; and how – and where – to it properly Mental models research 323 IJSHE 12,4 324 These concepts are particularly important given that a lack of knowledge about recycling is a common trait of non-recyclers (Schultz, 2002) The more knowledgeable an individual is about what items are recyclable, how to prepare items for recycling, and where to go to recycle, the more likely the individual is to correctly take part in the activity (Gamba and Oskamp, 1994; Vining and Ebreo, 1990; De Young, 1989; Scott, 1999) The good news for increasing community participation in university recycling programs is that a lack of knowledge about how to recycle appropriately may be overcome through education and outreach efforts The bad news is that, historically, many of these efforts have had only limited success because they have not adequately account for important characteristics – , e.g areas where people have a clear understanding of concepts as well as key gaps in knowledge – of the people they are trying to reach (Fishbein and Yzer, 2003; Fishbein and Cappella, 2006; Meneses, 2006) A particularly promising approach for empirically identifying knowledge gaps that ought to be the targets of outreach and education is known as mental models analysis (Morgan et al., 2002) Mental models are psychological representations of real or hypothetical situations and their theoretical underpinnings date back to early research in cognitive science At the time, mental models were viewed as representations of reality that could be used to anticipate events, reason, and underlie explanation (Craik, 1943) More recent work on mental models (Holland et al., 1986; Johnson-Laird, 1983) emphasizes their use as a tool for diagrammatically representing people’s perceptions and understanding of a wide variety of issues and concepts Applied to education and outreach efforts, mental models analysis is based on the notion that people tend to assemble their knowledge of risks into a conceptual map of ideas (i.e a mental model) After these models have been created, it becomes possible to compare them with an eye toward looking for important gaps in people’s knowledge Identifying these gaps allows analysts to systematically identify people’s specific information and related decision-making needs, and contribute to the development of a framework for a more efficient and effective communication strategy The mental models approach is an easily replicable methodology (see Morgan et al (2002) for a review) that has been applied in a variety of contexts; these include the health risks stemming from exposure to radon (Bostrom et al., 1992), nuclear power (Maharik and Fischhoff, 1993), dry-cleaning chemicals (Kovacs et al., 2001), and wildfire (Zaksek and Arvai, 2004) However, no studies to date have applied the mental models approach to questions of campus sustainability, including recycling programs This is not to suggest that no work has been conducted on this topic For example, there have been studies of how to specifically tailor recycling programs for communities on the basis of demographic variables such as income, ethnicity, and gender (Howenstine, 1993; Kaplowitz et al., 2009) But, relatively few studies have focused on systematically exploring the specific information needs of people regarding recycling programs To this end, this paper reports the results from research conducted to inform the design of education and outreach efforts aimed at, ultimately, increasing recycling rates on the MSU campus The objectives of this research were to: (1) develop a better understanding of the state of knowledge of students and faculty on the MSU campus; (2) identify relevant gaps in knowledge and misconceptions about recycling; and (3) provide recommendations regarding how these gaps and misconceptions may be addressed through education and outreach Mental models research Methods 2.1 Study area This research was conducted between 2007 and 2008 on the main campus of MSU, which is located in East Lansing, Michigan At the time of this study, a total of 46,045 students were enrolled at MSU; 36,072 of these were in undergraduate degree programs and 9,973 in graduate programs In addition to these students, approximately 4,800 faculty members work on campus 325 2.2 Subjects Because of their numbers and influence on campus – in terms of the amount of recyclable material they generate – students and faculty were identified by the university administration as priority targets for outreach efforts surrounding MSU’s new campus recycling initiative (Hansen et al., 2008)[1] Moreover, undergraduates living on campus were selected as one focus of this study because of their potential involvement in the widest range of campus recycling options Student subjects (n ¼ 40; a typical size for a mental models study) were recruited via mail; 250 letters were sent by the MSU’s Office of Vice President for Finance and Operations (VPFO), which is responsible for overseeing campus sustainability programs, to randomly selected students living in MSU residential halls In collaboration with MSU’s Department of Residence Life, four specific residential halls were identified for study because they were deemed to be representative of the range of residential living options (in terms of the diversity of the student residents and recycling options) on campus The letter sent to potential subjects briefly explained the purpose of the study and promised a monetary incentive of $40 for taking part The initial response rate was 64 per cent with 160 students responding to the letter; of these, 20 females and 20 males representing each of the four residential halls (i.e five females and five males per hall) were randomly selected for interviews The faculty sample (n ¼ 18), by contrast, was recruited using a randomized phone list of all faculty members working on campus The faculty sample consisted of 14 male and four female subjects randomly selected from buildings deemed by the Director of MSU’s Office of Recycling and Waste Management to be “recycling-friendly” (e.g buildings where there was adequate space and infrastructure available to carry out MSU’s proposed recycling activities) and “recycling unfriendly” (buildings where recycling is typically more difficult because space and infrastructure are inadequate) 2.3 Design Mental models analysis begins with the construction of a comprehensive technical, or “expert” model (Figure 1) This initial model was developed based on an extensive review of MSU policy documents and technical manuals as well as initial interviews with those individuals responsible for campus sustainability programs (specifically, MSU’s Sustainability Director, the municipal recycling coordinators from the neighboring communities of East Lansing, Michigan and Lansing, Michigan, and managers of the contracted commercial recycling hauler for MSU) The expert IJSHE 12,4 Steel Aliminum Scrap Cans Brown Clear Plastics Non-Fibers, "Containers" Pre Consumer White paper Sports Game Venues Residential Dining Dining/ Concessions Residence Hall #2 HDPE Colored Location on Campus Surplus Store Campus and Academic Buildings Reuse Garbage Location in Complex Campus owned Apartments Paper Mixed paper Location on Campus Careboard News paper Post Consumer Location in Buliding Magazines Paperboard Junk Mail Locations Alternatives Fibers Processing Facility Soft bound books Time Fabric Pre Consumer Recycling at MSU Items Batteries International Centre Sparty's Cafes #2 HDPE Cloudy Reduce 326 Location in Hall Glass Metal Post Consumer Location on Campus #1 PETE Foil Fluorescent Light Bulbs Ink Jet Cartridges Ease Disinccentives Impediments Convenience Specific Knowledge/ Instructions Space Pallets Leaves Fly Ash Other Environmental Benefits Benefits Logistics Water Grass Organic Materials Construction Waste Branches Food Waste Electronic Waste Shoes Toner Energy Social Benefits Tires Air Land Economic Benefits Manure SelfSorting Soft bound books Figure Expert model characterizing recycling on the MSU campus Pick-up Special Processing Facility Drop-off Method Awareness Tipping Fees Monetary Incentives Jobs Magazines Removing Inpurities Non-Fibers, "Containers" White Paper Quality Control Garbage Fees Deposit #1 PETE Paper Paper borad Brown Mixed Paper News Paper Glass Cardbord Clear Plastics Tin/ Aluminum #1 HDPE Cloudy Remove Caps Clean Signs Proper Sorting #2 HDPE Colored model included six general concept areas, each dealing with recycling on the MSU campus: A list of items that may be recycled (or composted) on the MSU campus Locations on the MSU campus where recyclable items may be delivered (e.g pick-up or drop-off points, processing facilities, etc.) Logistics, in terms of how items must be prepared (e.g cleaning, sorting, etc.) prior to recycling them at MSU The benefits of recycling at MSU and elsewhere Impediments to recycling on the MSU campus Alternatives to recycling on the MSU campus (e.g reducing the amount of waste material generated, reusing products that are meant to be disposable, etc.) Based on this expert model, a standardized, 50-question open-ended interview protocol was developed The same interview protocol was used for both the student and faculty subjects and took approximately between 30 and 80 minutes to administer ðx ¼ 45 minutesÞ Each interview was recorded for coding immediately following the interview The protocol was administered by the same facilitator – the first author, Olson – in all cases As with the expert model, the interview protocol was structured around the six general content areas accounting for recycling on the MSU campus These six categories were further subdivided into several associated content areas as illustrated by each branch of the expert model Each respondent was told that the interview protocol was designed to exhaust their awareness and knowledge about particular topic areas as it related to recycling on campus To this end, each subject was asked to answer a series of questions from each of the six specific content areas during the interview The first questions in a series were intentionally broad and were followed by more specific questions designed to exhaust a subject’s knowledge of each aspect of recycling For example, the first question in each interview was intentionally broad: What can you tell me about recycling at MSU? Subjects were encouraged to provide as much information as possible However, at this point, they were not prompted to specifically explore the six specific content areas As the interviews naturally progressed down each branch of the expert model, the questions became more specific, with the intent of eliciting concepts that a subject may have omitted despite being aware of them These follow-up questions also prompted the participant to draw conclusions and make inferences, based upon their pre-existing perceptions, regarding concepts that they may not have considered (per Morgan et al., 2002) For example, once participants had stated the various recyclable materials that initially came to mind (or indicated that none came to mind after the initial, broad question was asked), they were prompted with increasingly specific follow-up questions, such as: Now that you’ve talked about recyclable containers, are there other materials that may be recycled on campus? What about paper products? Are there any other kinds of paper or items made from paper that can be recycled on campus? When subjects indicated that they had exhausted their knowledge of the concept that was the focus of the questioning, the facilitator proceeded to the next series of questions 2.4 Analysis Immediately following each interview, a graphical mental model was developed for each subject based on the overall structure of the expert model Concepts mentioned by subjects that were absent from the expert model (including both valid beliefs and misconceptions) were incorporated and highlighted in these individualized models (Figure 2) Also, the answers obtained in response to each question in the interview protocol were coded (by the authors and two research assistants) using a five-point, categorical scoring scheme, which was extensively pre-tested for inter-coder reliability This scoring scheme utilized an ascending scale designed to reflect the level of knowledge of the participant regarding each of the concepts depicted in the expert model (i.e higher scores correspond with more accurate comprehension) Scores were assigned as follows: – subject was unable to answer interview question (i.e no information was provided) – a concept was discussed when prompted but misunderstood by subject – a concept was discussed without prompting but misunderstood by subject – a concept was discussed when prompted and understood by subject – a concept was discussed without prompting and understood by subject These scores were then used to estimate mean levels of knowledge for each concept present in the expert model (Tables I and II) A series of Pearson’s x tests were Mental models research 327 IJSHE 12,4 Steel Aluminum Scrap Cans Location in Hall Location on Campus Foil Sports Game Venues Glass Sparty's Cafes Plastics Metal Pre Consumer Residence Hall Dining/ Concessions Non-Fibers, "Containers" Location on Campus Campus and Academic Buildings White Paper 328 Location in Building Magazines Reuse Garbage Paperboard Paper Junk Mail Mixed Paper Cardboard Newspaper Locations Alternatives Fibers Soft bound books Time Post Consumer Recycling at MSU Items Ease Disincentives Impediments Convenience Specific Knowledge/ Instructions Logistics Benefits Energy Social Benefits SelfSorting Figure Sample individual model elicited from an MSU student Non-Fibers, "Containers" White Paper Pick-up Special Processing Facility Drop-off Removing Inpurities Air Quality Control Land Economic Benefits Awareness Method Space Environmental Benefits Monetary Incentives Garbage Fees Deposit Paper Clean Mixed Paper Newspaper Glass Plastics Signs Proper Sorting Cardboard conducted to test for significant differences in the distribution (frequency) of score categories[2] and, by extension, mean knowledge levels across each of the content areas represented in the expert model by sample (student and faculty) and gender (Table I), and by building location (Table II) Results 3.1 General trends By combining data from the individual mental models elicited from students and faculty members (Figure 2), an overall mental model that depicted the frequency with which subjects understood each concept – reflected in their receiving a score of or for each concept area; see above – was developed (Figure 3) This composite model revealed important gaps, on part of both MSU students and faculty, in understanding key recycling concepts that are relevant to established campus-based waste reduction practices Among many identified gaps – only a few of which will be described here for the sake of brevity – both students and faculty displayed an incomplete understanding of where different items could be recycled on campus (Figure 3) While students knew that recycling opportunities were present in academic buildings and campus dining areas, few knew of specific details regarding where else recycling opportunities were available on campus For example, only a small percentage of students knew of specific collection points for recyclables at on-campus sports venues (22.5 per cent), the International Center food court (10 per cent), residential dining areas (40 per cent), and campus cafe´s (12.5 per cent) The same was true of MSU faculty members 0.24 0.41 0.20 0.37 0.32 0.21 0.40 0.27 0.05 0.37 0.22 0.36 0.17 0.08 0.26 0.11 0.11 0.37 011 0.37 3.35 1.61 3.80 1.05 3.20 3.65 1.71 3.20 3.95 1.05 3.55 2.31 3.45 3.85 2.85 3.55 3.65 2.70 3.55 2.05 3.55 3.05 3.60 2.30 3.80 3.05 3.61 3.51 2.45 3.52 0.55 3.45 2.21 3.60 3.90 3.75 2.25 3.85 0.91 3.33 0.11 0.31 0.11 0.36 0.08 0.28 0.41 0.25 0.34 0.22 0.21 0.28 0.42 0.11 0.07 0.10 0.43 0.08 0.36 0.23 n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s x2 4.00 2.00 3.00 2.50 4.00 4.00 2.75 0.50 1.00 4.00 1.75 4.00 0.75 3.17 3.75 3.50 3.50 4.00 3.50 1.00 0.07 0.15 0.95 0.87 0.07 0.06 0.95 0.29 0.71 0.02 0.98 0.65 0.21 0.43 0.98 0.05 0.05 0.01 0.29 0.01 3.64 2.80 3.00 1.29 3.86 3.29 2.43 0.50 1.29 4.00 1.71 3.50 1.57 1.50 3.21 4.00 3.93 3.64 2.71 2.43 0.13 0.45 0.36 0.42 0.56 0.46 0.29 0.29 0.45 0.01 0.47 0.38 0.29 0.87 0.48 0.21 0.34 0.01 0.29 0.35 Faculty Female Male x SE x SE ** n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s n/s ** ** n/s *** n/s n/s n/s * x2 3.60 2.88 3.58 2.18 3.83 2.95 3.58 3.53 2.38 3.48 0.80 3.55 1.95 3.40 3.93 3.55 1.93 3.83 0.98 3.25 0.08 0.24 0.08 0.26 0.06 0.20 0.08 0.16 0.24 0.13 0.24 0.17 0.29 0.15 0.04 0.13 0.30 0.11 0.26 0.20 Students x SE 0.08 0.09 0.23 0.39 0.46 0.23 0.38 0.32 0.30 0.43 0.23 0.38 0.01 0.08 0.39 0.27 0.11 0.42 0.34 0.39 3.89 3.83 3.72 2.89 2.11 3.61 1.39 2.78 3.33 1.72 0.50 1.22 4.00 3.89 2.50 3.44 3.72 2.39 3.00 1.56 Overall Faculty x SE n/s * n/s n/s n/s n/s n/s *** ** * n/s * * n/s n/s *** ** n/s ** n/s x2 Notes: *p ¼ 0.05; * *p ¼ , 0.01; * * *p ¼ , 0.001; means were compared using t-tests (see Section 3.2); x tests of significance across frequencies for each score category (0-4; not shown) are also summarized Paper White Mixed Newsprint Glossy Cardboard Containers Aluminum Steel Glass Plastic Other E-waste key locations Residence halls Dining areas Academic buildings Benefits Environmental Social Economic Logistics Paper sorting Glass sorting Plastic sorting Rinsing/cleaning Students Female Male x SE x SE Mental models research 329 Table I Mean knowledge level across 20 major concept areas by sample (student and faculty) and gender IJSHE 12,4 330 Table II Mean knowledge level across 20 major concept areas by residence hall Hall x SE Paper White Mixed Newsprint Glossy Cardboard Containers Aluminum Steel Glass Plastic Other E-waste key locations Residence halls Dining areas Academic buildings Benefits Environmental Social Economic Logistics Paper sorting Glass sorting Plastic sorting Rinsing/cleaning Residential halls (students) Hall Hall Hall x SE x SE x SE x2 Academic buildings (faculty) “Unfriendly” “Friendly” x SE x SE x2 3.30 2.20 3.90 0.30 3.40 0.40 0.61 0.10 0.30 0.27 3.40 1.00 4.00 0.40 3.60 0.31 0.52 0.00 0.42 0.16 3.80 2.40 4.00 1.00 3.10 0.13 0.60 0.00 0.52 0.53 3.70 2.10 3.40 2.20 3.60 0.15 0.64 0.40 0.61 0.50 n/s n/s n/s n/s n/s 4.00 3.67 3.56 3.11 2.11 0.00 0.17 0.44 0.42 0.68 4.00 4.00 3.89 2.67 2.11 0.00 0.00 0.11 0.67 0.66 n/s n/s n/s n/s n/s 3.60 2.10 3.60 3.90 0.40 0.59 0.16 0.10 3.40 2.00 3.40 3.90 0.40 0.56 0.31 0.10 3.90 2.10 3.50 4.00 0.10 0.59 0.17 0.00 3.30 1.60 3.10 3.90 0.41 0.65 0.46 0.08 n/s n/s n/s n/s 3.44 1.78 2.67 3.44 0.44 0.57 0.53 0.44 3.78 1.00 2.89 3.22 0.15 0.50 0.39 0.43 n/s n/s n/s n/s 1.10 0.57 0.70 0.47 1.00 0.52 0.40 0.39 n/s 1.89 0.61 1.56 0.63 n/s 3.90 0.10 3.00 0.45 3.50 0.41 3.50 0.31 n/s 2.30 0.52 2.40 0.54 2.40 0.48 2.40 0.47 n/s 3.00 0.26 3.90 0.10 3.60 0.16 3.40 0.41 n/s 1.32 1.89 4.00 0.38 0.61 0.00 0.90 0.56 4.00 0.39 n/s 0.34 n/s 0.00 n/s 3.80 0.13 3.90 0.10 3.80 0.13 3.81 0.57 n/s 2.70 0.40 2.90 0.50 3.00 0.37 3.20 0.39 n/s 3.50 0.17 3.60 0.16 3.62 0.17 3.66 0.19 n/s 4.00 2.56 3.89 0.00 0.58 0.11 3.78 2.44 3.00 0.15 n/s 0.56 n/s 0.50 n/s 3.60 3.30 3.70 2.40 3.67 2.33 2.89 1.78 0.17 0.60 0.56 0.57 3.78 2.44 3.11 1.33 0.15 0.63 0.44 0.55 0.16 0.40 0.15 0.54 3.40 2.70 3.30 1.60 0.16 0.47 0.14 0.54 3.90 2.60 3.70 2.40 0.10 0.58 0.15 0.48 3.50 2.90 3.61 2.30 0.17 0.50 0.16 0.52 n/s n/s n/s n/s n/s n/s n/s n/s Notes: *p ¼ 0.05; * *p ¼ ,0.01; * * *p ¼ , 0.001; (labeled Halls through with means compared using Analysis of Variance; see Section 3.2) and academic building (labeled recycling “friendly” and “unfriendly with means compared using Analysis of Variance; see Section 3.2); x2 tests of significance across frequencies for each score category (0-4; not shown) are also summarized interviewed; relatively few faculty members were aware of collection points for recyclables in dining and concession areas (33.3 per cent) And, neither students (5 per cent) nor faculty (11.1 per cent) were well aware of recycling opportunities at the general campus recycling facility There were also distinct gaps in knowledge among students and faculty about the range of items that can be recycled on campus For example, while all students and faculty knew that “paper” could be recycled on campus, relatively few were aware of many common but more specific paper products that are recyclable; these included low levels of understanding by students and faculty regarding the fact that soft-bound books (25 and 2.5 per cent, respectively) and telephone directories (27.8 and 38.9 per cent, respectively) are recyclable on-campus A similar trend was observed among students and faculty regarding the recycling of junk mail (40 and 11.1 per cent, respectively) and paperboard (0 and 12.5 per cent, respectively) On a positive note, both students and faculty were well aware of newspaper recycling opportunities on campus (97.5 and 94.4 per cent, respectively) In terms of recyclable containers, a high level of general knowledge was evident for both students and faculty but more specific knowledge tended to be relatively weak Steel 55.0/44.4 Scrap 47.5/50.0 Aluminum 92.5/94.4 Clear 42.5/55.6 Foil 17.5/27.8 #1 PETE 82.5/66.7 Brown 15.0/38.9 Cans Glass 92.5/83.3 Plastics 100/88.9 Metal 97.5/94.4 Pre-Consumer 5.0/5.6 Post-Consumer 82.5/61.1 White paper 95.0/100.0 Non-Fibers, "Containers" Litter 15.0/11.1 Post-Consumer 77.5/33.3 Campus and Academic Buildings 95.0/100.0 Fluorescent Light Bulbs 2.5/11.1 Ink Jet Cartridges 25.0/38.9 Locations Processing Facility 5.0/11.1 Recycling at MSU Items Impediments Food Waste 25.0/5.6 Manure 12.5/11.1 Soft bound books 5.0/11.1 Electronic Waste 22.5/50.0 Logistics Tires 15.0/0.0 Paper borad 2.5/0.0 Brown 17.5/27.8 Cardbord 42.5/33.3 Benefits Clear 20.0/38.9 Deposit 12.5/0.0 Non-Deposit 12.5/0.0 Non-Fibers, "Containers" 77.5/88.9 Glass 80.0/66.7 Energy 37.5/44.4 Food Oil 2.5/0.0 Self-Sorting 87.5/100.0 Paper 100.0/100.0 Mixed Paper 45.0/94.4 News Paper 62.5/55.6 Toner 2.5/16.7 Magazines 7.5/44.4 White Paper 50.0/94.4 Environmental Benefits 100.0/100.0 Construction Waste 12.5/0.0 Shoes 5.0/11.1 Convenience 92.5/88.9 Specific Knowledge/ Instructions 95.0/72.2 Other Oraganic Materials 40.0/27.8 Ease 85.0/66.7 Disinccentive 97.5/100.0 Fly Ash 0.0/0.0 Grass 17.5/5.6 331 Location on Campus 0.0/0.0 Time 82.5/50.0 Loft Wood 7.5/0.0 Pallets 2.5/0.0 Branches 10.0/0.0 Location in Complex 0.0/0.0 Campus owned Apartments 0.0/0.0 Batteries 30.0/22.2 Leaves 12.5/5.6 Location in Buliding 87.5/94.4 Garbage 100.0/100.0 Reuse 9205/83.3 Location on Campus 92.5/94.4 Fabric 15.0/5.6 Pre-Consumer 2.5/0.0 Motor Oil 10.0/5.6 Union 7.5/0.0 Surplus Store 2.5/50.0 Alternatives Fibers 5.0/0.0 Phone Books 2.5/38.9 Soft bound books 25.0/27.8 Mental models research International Centre 10.0/22.2 Residential Dining 40.0/16.7 Paper 100.0/100.0 Mixed paper 50.0/100.0 News paper 97.5/94.4 Sports Game Venues 22.5/11.1 Dining/ Concessions 67.5/33.3 Residence Hall 90.0/11.1 Reduce 47.5/38.9 Magazines 27.53/77.8 Location in Hall 87.5/5.6 Sparty's Cafes 12.5/16.7 #2 HDPE Colored 15.0/11.1 Careboard 85.0/55.6 Paperboard 12.5/0.0 Junk Mail 40.0/11.1 Location on Campus 87.5/5.6 #2HDPE Cloudy 55.0/50.0 Plastics 100.0/83.3 Tin/Aluminum 80.0/77.8 #1 PETE 40.0/55.6 #2 HDPE Cloudy 30.0/33.3 #2 HDPE Colored 15.0/11.1 Processing Facility Drop-off 62.5/11.1 Land 50.0/77.8 Extraction Costs 10.0/11.1 Sale of Surplus items/Materials 2.5/0.0 Method Awareness Removing Inpurities 75.0/61.1 Remove Caps 32.5/27.8 Water 32.5/16.7 Air 47.5/22.2 Economic Benefits 100.0/88.9 Social Benefits 85.0/66.7 Pick-up 67.5/50.0 Space 22.5/22.2 Quality Control 90.0/94.4 Tipping Fees 25.0/16.7 Jobs 32.5/33.3 Monetary Incentives 92.5/88.9 Garbage Fees 15.0/27.8 Deposit 90.0/83.3 Clean 65.0/38.9 Signs 45.0/50.0 Proper Sorting 82.5/94.4 Notes: Values indicate percent understanding, reflected by scores of or 4, across both student (first value) and faculty (second value) respondents; hatched boxes depict correct concepts that were not present in the initial expert model For example, beyond the general knowledge that different categories of containers (plastics, glass, and metals) are recyclable on campus, only 55 per cent of students and 44 per cent of faculty interviewed indicated an awareness about the recyclability of common steel cans used primarily for food products This result stood in contrast to reported knowledge by students and faculty about aluminum beverage cans (93 and 94 per cent, respectively) and No PETE plastic used in most soda and water bottles (82.5 and 66.7 per cent, respectively) Subjects also struggled with questions about how recycling must be carried out on the MSU campus While students and faculty were well aware of the strict separation rules in place at MSU (with 82.5 per cent of students and 94.4 per cent of faculty understanding the requirement of sorting different categories of recyclable materials), they were much less knowledgeable about the specific details of this process Beyond knowing that certain categories of items need to be separated from one another –, e.g paper, metals, and glass – few subjects knew that different types of plastic and paper had to be separated further Further, relatively few student and faculty subjects knew that containers must be thoroughly cleaned, and caps and lids removed, prior to their being deposited at a recycling station A similar trend was observed regarding stated knowledge about why recycling is important on the MSU campus While students and faculty seemed to generally Figure Composite student and faculty mental model IJSHE 12,4 332 understand that recycling is beneficial for economic (100 and 88.9 per cent, respectively), social (85 and 66.7 per cent, respectively), and environmental (100 per cent for both groups) reasons, few specifics were provided by either subject group For example, understanding the relationship between recycling and related concepts such as energy conservation, air quality, and water quality were not mentioned by a majority of MSU students (37.5, 47.5, 32.5 per cent, respectively) and faculty (44.4, 22.8, 16.7 per cent, respectively) As far as impediments to recycling were concerned, these were relatively well understood by both students and faculty; the only significant exception was a relatively low level of knowledge displayed by both students and faculty (approximately 22.2 per cent for both groups) regarding space constraints for recycling services in many campus buildings Notably, a lack of knowledge about specific instructions – how, what, where, and why – was identified as a significant impediment to their participation in campus recycling programs by 95 per cent of students and 72 per cent of faculty interviewed In addition to recycling, faculty and students were generally aware that there are several alternatives to recycling on MSU’s campus; the most well known of these alternatives is the placement of recyclables in trash bins (which was discussed by all students and faculty members that were interviewed) This strategy was followed closely by the option to reuse many items for purposes related to their initial design (e.g refilling plastic containers) However, the concept that people – including university purchasers – may make decisions to use only those products that yield less waste (e.g packaging) was identified relatively infrequently by MSU students and faculty (47.5 and 38.9 per cent, respectively) 3.2 Results from significance tests Significance testing was conducted across mean knowledge levels for all 120 content areas (Figure 3) with specific comparisons made by sample and gender (using t-tests), and by building location (using analysis of variance) The results of comparisons for a subset of 20 content areas, judged by managers of MSU’s recycling program to of particular interest, are shown here (Tables I and II) In terms of differences by sample (Table I), students that took part in this research had a higher level of understanding across five content areas; these included an awareness of recycling opportunities for cardboard ( p , 0.01), glass ( p ¼ 0.05), and plastic containers ( p ¼ 0.05) Likewise, student participants had a better understanding of the need to sort different types of plastic containers ( p ¼ 0.05), and of specific recycling opportunities in residential buildings ( p , 0.001) and dining areas ( p , 0.01) on campus Faculty participants, by contrast, had a better understanding of the need to separate different types of paper – mixed ( p , 0.01) and glossy ( p , 0.001) – and had a greater level of awareness with respect to recycling opportunities in campus academic buildings ( p ¼ 0.05) Gender differences (Table I) were identified only in the faculty sample Female faculty members possessed a better understanding of recycling opportunities for glass ( p , 0.001) and were more knowledgeable about the need to clean containers prior to depositing them at collection points for recyclables ( p , 0.01) Male faculty participants, on the other hand, displayed a greater level of awareness of recycling opportunities for white paper ( p , 0.01), cardboard ( p , 0.001), and steel containers ( p , 0.01) No statistically significant differences were detected in the comparison of student responses across the four residential halls studied; the same was true of faculty comparisons by two categories – recycling “friendly” and “unfriendly” – of academic building (Table II) Discussion After discussing these findings with MSU’s Office of the VPFO, the sponsor of this study and responsible office for the campus recycling initiative, four key knowledge gaps were identified as important targets for outreach and education efforts aimed at the campus community First, and foremost, significant knowledge gaps within and between student and faculty groups regarding the range of materials that are recyclable on the MSU campus were observed (Figure 3) A lack of detailed knowledge regarding some of these items – , i.e those that are outside the sphere of influence of many study participants (e.g organic materials, light bulbs, scrap metal from construction) – was deemed to be acceptable However, other items – including specific knowledge about how to identify and differentiate them – were judged to be too common and important for the campus community to remain uninformed about in terms of their place within the campus recycling stream For example, many common paper types – , e.g mixed and glossy paper, cardboard and paperboard – were the subject of unacceptably low levels of mean knowledge on the part of either, and sometimes both, the students and faculty members that were interviewed The same was true of both common container types and other widely used materials (such as toner and inkjet cartridges, as well as other forms of electronic waste) with low frequencies of understanding, low mean levels of knowledge, and statistically significant differences between groups observed across both samples (Tables I and II, Figure 3) Second, locations at MSU where recyclable materials may be deposited were generally not well known by participants in this research beyond the places where they spent the majority of their time on campus; this included residential halls and campus dining areas for undergraduate students, and academic buildings for faculty Though students who lived off campus were included in the analysis, it is likely that this trend would be observed for them as well, specifically in the direction of more detailed knowledge about recycling opportunities in academic buildings (including classrooms and common areas) and on-campus dining areas To some degree, this finding was expected in the sense that students who live on campus should be more knowledgeable than faculty about recycling opportunities in residential areas and dining areas – with the opposite being true for faculty members (Table I) The problem with this trend, however, is that faculty members at MSU tend to frequent both campus dining areas (e.g food courts in the Student Union Building and International Center, restaurant-style dining halls in residential buildings, and university-owned cafe´ s) and residential halls (because most of them also contain classroom and conference facilities) As a result, it was decided that faculty – and to a lesser degree, students – should be made more aware of recycling opportunities in these areas And from the standpoint of both students and faculty, it was also decided that both groups should be made more aware of recycling opportunities at other popular gathering areas on campus, such as sports venues like Spartan Stadium (football), the Breslin Center (basketball), and the Munn Ice Arena (ice hockey) Mental models research 333 IJSHE 12,4 334 In general, it was concluded that the notion of recycling as an activity that can and should be done virtually anywhere and anytime on campus needs reinforcement among members of the campus community Third, the findings reported here suggest that there is a relatively low level of knowledge among members of the MSU community about the logistics associated with preparing materials for recycling (e.g the need to sort different containers, paper products, etc.) For example, while student and faculty participants knew generally that plastic containers are recyclable on campus, few knew that plastic caps and lids should not be introduced to the recycling stream (Figure 3) Though no statistical differences by gender, sampling population, or location on campus were detected, this recommendation is based on the generally low frequency with which study participants discussed this content area (Figure 3), and the low mean knowledge level associated with it (Table II); this, in turn, underscores the importance of tracking multiple kinds of data in a study of this type Fourth, while MSU students and faculty members were knowledgeable about reusing materials as an alternative to waste generation and recycling at MSU, they possessed a relatively low level of comprehension with respect to waste reduction practices (Figure 3) Because of the university’s high purchasing power at both the student and faculty levels, it was recommended that a key element of the education and outreach effort associated with MSU’s expanded recycling program be a focus on encouraging the MSU community to account for waste reduction during consumer decision-making For example, messages may focus on encouraging faculty and staff to make bulk purchases (e.g for hardware, field and lab equipment, etc.) from manufacturers who provide a reduced packaging option; likewise, both students and faculty may be encouraged to purchase more durable and efficient products, while also making more efficient use of existing equipment (e.g duplex printing) In sum, the mental models approach deployed in this study was the first step in a long-range process to educate the MSU community about, and to involve the community in, the rollout of an expanded campus recycling program Currently, the VPFO’s office is actively engaged in developing and deploying educational and outreach resources aimed at the campus community Based on these findings, some of these are being targeted to specific types of building – academic and residential – and specific members of the campus community such as students, staff, and faculty Discussing each of these initiatives is beyond the scope of this paper However, a number of examples of different education and outreach resources that have since been developed at MSU may be viewed on the internet (at: www.recycle.msu.edu) From a methodological standpoint, the mental models approach has been embraced by university administrators because of the way it meaningfully engages members the MSU community in the ultimate design of education and outreach efforts for recycling Unlike a survey, or a conventional interview (or focus group) protocol that is based on asking people what they’d like to know, the mental models approach overcomes common obstacles to validity while being more thorough and systematic in its application For example, because of its focus on eliciting what psychologists refer to as a “core dump” of existing knowledge, beliefs, and inferences, the mental models approach minimizes the risk that the interview process itself will provide unintended cues to study participants regarding correct or desired responses In other words, the mental models approach does not provide participants with an opportunity to try and discern the underlying meaning of interview questions or what the interviewer might expect them to say (Morgan et al., 2002); this, in turn, reduces the probability that participants selected to take part in a mental models study will no longer represent the population from which they were sampled (e.g students and faculty in this case) However, it is important to note that one of the possible shortcomings of the mental models approach applies to the generalizability of the results Because of the relatively small number of participants interviewed, researchers cannot be certain that the population shares the characteristics identified in a given sample In the case of the research reported here, a decision was made (by the authors and the project sponsors) to employ the mental models approach over survey so that depth of understanding could be emphasized in addition to depth during information gathering Related, the mental models approach was selected because it was found during pretesting to feel less like a “knowledge test” to participants when compared with a conventional survey Nevertheless, to support this research a small-scale confirmatory survey (as part of a separate research initiative focused on items that may be recycled on the MSU campus) was conducted; all of the findings from this follow-up survey supported the conclusions of the mental models analysis So as to increase face validity, we recommend the mental models approach be coupled with confirmatory survey to validate key findings among members of the population form which samples are drawn Conclusion Reinvention of the wheel is a common characteristic of many public outreach and education efforts that focus on sustainability, often for what may seem like good reasons In the case of new or expanded recycling and waste reduction programs, for example, it seems sensible to start at the beginning by alerting people to basic issues and considerations;, e.g the scope of the problem that is the focus of new management efforts, the benefits of behavior change, and logistical information to facilitate compliance with whatever new initiative is being implemented On the flipside, however, starting at the beginning during public outreach and education efforts may come at a significant cost to program managers On the one hand, simply rehashing information that is already well known to project participants risks making new programs sound like older ones As a result, new initiatives may become lost in the morass of existing programs, thereby creating an unnecessary barrier to adoption And, the expenditure of limited resources – time, funding, etc – by program managers or outreach specialists on information that people already have or understand means that even fewer resources will be available to tell people what they really need or want to know To this end, the mental models approach, as exemplified by the research focused on recycling at MSU, provides program managers and outreach specialists with a constructive and transparent tool for developing and deploying program information that builds on existing knowledge while also meeting the new information needs of people This is a step in the right direction toward thoughtfully designed outreach and education efforts Notes University staff members were, while also important members of the campus community in terms of their potential contribution to recycling efforts, not included in this research Mental models research 335 IJSHE 12,4 336 Instead, university staff were involved in a separate, focus-group-based research effort to establish programmatic needs For female representatives of the MSU faculty, sample sizes were amplified using the Monte Carlo method for sample approximation References Bostrom, A., Fischhoff, B and Morgan, M.G (1992), “Characterizing mental models of hazardous processes: a methodology and an application to radon”, Journal of Social Issues, Vol 48, pp 85-100 Craik, K (1943), The Nature of Explanation, Cambridge University Press, Cambridge De Young, R (1989), “Exploring the difference between recyclers and non-recyclers: the role of information”, Journal of Environmental Systems, Vol 18 No 4, pp 341-51 Fishbein, M and Cappella, J.N (2006), “The role of theory in developing effective health communications”, Journal of Communication, Vol 56, pp S1-S17 Fishbein, M and Yzer, M.C (2003), “Using theory to design effective health behavior interventions”, Communication Theory, Vol 13, pp 164-83 Gamba, R.J and Oskamp, S (1994), “Factors influencing community residents’ participation in commingled curbside recycling programs”, Environment & Behavior, Vol 26 No 5, pp 587-612 Hansen, L.T., McMellen, C., Olson, L., Kaplowotz, M., Kerr, J and Thorp, L (2008), “Recycling attitudes and behaviors on a college campus: use of qualitative methodology in a mixed-methods study”, Journal of Ethnographic and Qualitative Research, Vol 2, pp 173-82 Holland, J.H., Holyoak, K.J., Nisbett, R.E and Thagard, P.R (1986), Induction: Processes of Inference, MIT Press, Cambridge, MA Howenstine, E (1993), “Market segmentation for recycling”, Environment & Behavior, Vol 25 No 1, pp 86-102 Johnson-Laird, P.N (1983), Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness, Cambridge University Press, Cambridge Kaplowitz, M.D., Yeboah, F.K., Thorp, L and Wilson, A.M (2009), “Garnering input for recycling communication strategies at a Big Ten University”, Resources, Conservation and Recycling, Vol 53 No 11, pp 612-23 Kovacs, D.C., Fischhoff, B and Small, M.J (2001), “Perceptions of PCE use by dry cleaners and dry cleaning customers”, Journal of Risk Research, Vol 4, pp 353-75 Maharik, M and Fischhoff, B (1993), “Risk knowledge and risk attitudes regarding nuclear energy sources in space”, Risk Analysis, Vol 13, pp 345-53 Meneses, G.D (2006), “How to teach recycling at an advanced phase of diffusion”, Journal of Environmental Education, Vol 37 No 4, pp 19-32 Morgan, M.G., Fischhoff, B., Bostrom, A and Atman, C.J (2002), Risk Communication: A Mental Models Approach, Cambridge University Press, Cambridge Pike, L., Shannon, T., Lawrimore, K., McGee, A., Taylor, M and Lamoreaux, G (2003), “Science education and sustainability initiatives: a campus recycling case study shows the importance of opportunity”, International Journal of Sustainability in Higher Education, Vol No 3, pp 218-29 Schultz, P.W (2002), “Knowledge, information, and household recycling: examining the knowledge-deficit model of behavior change”, in Dietz, T (Ed.), New Tools for Environmental Protection, Academy Press, Washington, DC Scott, D (1999), “Equal opportunity, unequal results, determinants of household recycling intensity”, Environment & Behavior, Vol 31 No 2, pp 267-90 Vining, J and Ebreo, A (1990), “What makes a recycler? A comparison of recyclers and nonrecyclers”, Environment & Behavior, Vol 22 No 1, pp 55-73 Zaksek, M and Arvai, J.L (2004), “Toward improved communication about wildland fire: mental models research to identify information needs for natural resource management”, Risk Analysis, Vol 24, pp 1503-14 About the authors Lauren Olson is the Project Coordinator in the Office of Campus Sustainability at Michigan State University (MSU) Her work involves coordinating the Environmental Stewards Program, which seeks to involve many departments and units on campus to assist MSU in reaching its goals of decreased waste, increased recycling, and reduced energy consumption Lauren also leads the effort to help MSU become “green-certified” which is a new MSU program to recognize and assist units and students who are taking steps to reduce their environmental footprint Lauren possesses a BS in Environmental Economics and Policy and an MS in Community, Agriculture, Recreation, and Resource Studies; both degrees are from Michigan State University Joseph Arvai is a Professor and the Svare Chair in Applied Decision Research in the Haskayne School of Business and the Institute for Sustainable Energy, Environment, and Economy at the University of Calgary His research focuses on how people make decisions – both as individuals and in groups – largely in the absence of formalized decision support Informed by this work, a related objective of his research is to develop and test decision aids that can be used by people to improve decision quality across a variety of contexts Joseph Arvai is the corresponding author and can be contacted at: arvai@ucalgary.ca Laurie Thorp holds a PhD in Agricultural Education from Texas A&M University She is the Director of the Residential Initiative on the Study of the Environment, a living/learning community at Michigan State University She is also the co-director of the newly launched sustainability specialization at MSU This interdisciplinary program is co-sponsored by five colleges and is designed as a competency-based approach to learning Students provide evidence of skills in an electronic portfolio system Laurie has served on the MSU Environmental Stewardship Systems Team for the Vice President of Finance and Operations at MSU, and as technical team leader for behavioral research associated with various strategic change initiatives advancing increased environmental stewardship on MSU’s campus She also holds an adjunct appointment in the Department of Community Agriculture, Recreation and Resource Studies To purchase reprints of this article please e-mail: reprints@emeraldinsight.com Or visit our web site for further details: www.emeraldinsight.com/reprints Mental models research 337 ... as mental models analysis (Morgan et al., 2002) Mental models are psychological representations of real or hypothetical situations and their theoretical underpinnings date back to early research. .. Systems Team for the Vice President of Finance and Operations at MSU, and as technical team leader for behavioral research associated with various strategic change initiatives advancing increased... Residence Hall #2 HDPE Colored Location on Campus Surplus Store Campus and Academic Buildings Reuse Garbage Location in Complex Campus owned Apartments Paper Mixed paper Location on Campus Careboard