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

Mental models research to inform community outreach for a campus recycling program Lauren Olson Office of Campus Sustainability, Michigan State University, East Lansing, Michigan, USA Jo

Mental models research to inform community outreach for a campus

recycling program

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

www.emeraldinsight.com/1467-6370.htm

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 do not necessarily reflect the views of the sponsor

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Received 10 August 2010

Revised 1 February 2011

Accepted 25 February 2011

International Journal of Sustainability

in Higher Education

Vol 12 No 4, 2011

pp 322-337

q Emerald Group Publishing Limited

1467-6370

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 1 PETE (clear) and No 2 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 do 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 do it properly

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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

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(3) provide recommendations regarding how these gaps and misconceptions may

be addressed through education and outreach

2 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

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

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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

Figure 1.

Expert model

characterizing recycling

on the MSU campus

Glass

Plastics

Non-Fibers,

"Containers"

#1 PETE

#2 HDPE Cloudy

#2 HDPE Colored Surplus Store

Reduce Reuse Garbage

Location on Campus Location in Hall

Residence Hall

Dining/

Concessions

Venues Residential Dining International Centre

Sparty's Cafes

Location on Campus

Location on Campus

Time

Disinccentives

Specific Knowledge/

Instructions

Ease

Space

Water Environmental Benefits

Economic Benefits Social

Benefits

Benefits Impediments

Locations Alternatives

Items

Logistics

Recycling

at MSU

Method

Tipping Fees Awareness

Quality Control Removing Inpurities

Clean

Signs Proper Sorting

Remove Caps

#1 PETE

#1 HDPE Cloudy

#2 HDPE Colored

Jobs Monetary Incentives

Deposit Garbage Fees

Land Air Energy

Convenience

Location in Buliding Campus and Academic

Campus owned Apartments

Processing Facility

Location in Complex

Scrap Cans Foil

Metal

Post Consumer ConsumerPre

Post Consumer Pre Consumer

Batteries Ink Jet Cartridges Fluorescent

Pallets Leaves

Magazines

Grass

Branches

Food Waste

Manure

Organic Materials

Electronic Waste

Soft bound books White Paper Paper borad Mixed Paper News Paper

Paper Brown

Clear Glass Plastics

Non-Fibers,

"Containers"

Self-Sorting Pick-up Special Processing Facility Drop-off

Tin/

Aluminum Cardbord

Magazines Shoes Toner Tires

Other Fly Ash

Construction Waste

Paperboard

Mixed paper

News paper Soft bound books Junk Mail

Paper

Fibers

Fabric Careboard

White paper

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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:

0 – subject was unable to answer interview question (i.e no information was

provided)

1 – a concept was discussed when prompted but misunderstood by subject

2 – a concept was discussed without prompting but misunderstood by subject

3 – a concept was discussed when prompted and understood by subject

4 – 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 x2 tests were

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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)

3 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 3 or 4 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

Figure 2.

Sample individual model

elicited from an

MSU student

Cans Scrap

Pre Consumer

White Paper

Mixed Paper

Soft bound books Post

Consumer

Foil

Non-Fibers,

"Containers"

Self-Sorting Pick-up Special

Removing Inpurities Quality Control

Social Benefits EconomicBenefits

Proper Sorting

Garbage Fees

Monetary Incentives Processing

Facility Drop-off

Non-Fibers,

"Containers"

Metal

Magazines

Fibers

White Paper

Paper

Glass Plastics

Method

Signs

Awareness

Clean

Cardboard Mixed Paper Newspaper

Cardboard Junk Mail

Newspaper

Paperboard

Paper

Plastics

Reuse

Items

Logistics

Impediments

Benefits

Recycling

at MSU

Locations Alternatives

Location on Campus

Location on Campus

Location in Building

Environmental Benefits

Location in Hall

Residence Hall

Dining/

Concessions

Sparty's Cafes Venues

Campus and Academic

Garbage

Time

Disincentives

Specific Knowledge/

Instructions

Ease

Space

Energy Air Land

Deposit Convenience

Glass

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Paper White

Containers Aluminum

Other E-waste

Benefits Environmental

Logistics Paper

* p¼

2 tests

Table I Mean knowledge level across 20 major concept areas by sample (student and faculty) and gender

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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

Paper

Containers

Other

key locations

Benefits

Logistics

Notes: * p ¼ 0.05; * * p ¼ , 0.01; * * * p ¼ , 0.001; (labeled Halls 1 through 4 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); x2tests of significance across frequencies for each score category (0-4; not shown) are also summarized

Table II.

Mean knowledge level

across 20 major concept

areas by residence hall

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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 1 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 3 Composite student and faculty mental model.

Steel

55.0/44.4

Aluminum

92.5/94.4

Scrap 47.5/50.0 Cans

Glass 92.5/83.3 Plastics 100/88.9 82.5/66.7

#2HDPE Cloudy 55.0/50.0

#2 HDPE Colored 15.0/11.1 Metal

97.5/94.4

Benefits Impediments

Locations Alternatives

Items

Logistics

Recycling

at MSU

Foil 17.5/27.8 Clear 42.5/55.6 Brown 15.0/38.9

Non-Fibers,

"Containers"

Reduce 47.5/38.9 Reuse 9205/83.3 Garbage 100.0/100.0 Litter

15.0/11.1

Surplus Store 2.5/50.0

Location on Campus Location inHall 87.5/5.6

Residence Hall 90.0/11.1

Dining/

Concessions 67.5/33.3

Sports Game Venues 22.5/11.1 Residential Dining 40.0/16.7 International Centre 10.0/22.2 Sparty's Cafes 12.5/16.7 Union 7.5/0.0 Location on Campus 92.5/94.4

Location on Campus 0.0/0.0

Time 82.5/50.0

Disinccentive 97.5/100.0 Specific Knowledge/

Instructions 95.0/72.2

Ease 85.0/66.7

Space 22.5/22.2

Water 32.5/16.7 Environmental Benefits 100.0/100.0

Economic Benefits 100.0/88.9 Social

Benefits 85.0/66.7

Method

Tipping Fees 25.0/16.7 Awareness

Quality Control 90.0/94.4 Removing Inpurities

Clean 65.0/38.9 Signs 45.0/50.0 Proper Sorting 82.5/94.4

Remove Caps 32.5/27.8

#1 PETE 40.0/55.6

#2 HDPE Cloudy 30.0/33.3

#2 HDPE Colored 15.0/11.1

Jobs 32.5/33.3 Monetary Incentives 92.5/88.9

Extraction Costs 10.0/11.1 Sale of Surplus items/Materials 2.5/0.0

Deposit 90.0/83.3 Garbage Fees 15.0/27.8

Land 50.0/77.8 Air 47.5/22.2 Energy 37.5/44.4

Convenience 92.5/88.9

Location in Buliding 87.5/94.4

Campus and Academic 95.0/100.0

Campus owned Apartments 0.0/0.0

Processing Facility 5.0/11.1

Location in Complex 0.0/0.0

Post-Consumer

82.5/61.1

Pre-Consumer

5.0/5.6

Post-Consumer

77.5/33.3

Pre-Consumer

2.5/0.0

Ink Jet

Cartridges

25.0/38.9

Leaves

12.5/5.6

Magazines

Grass

17.5/5.6

Branches

10.0/0.0

Food

Waste

25.0/5.6

Manure

12.5/11.1

Electronic

Waste

22.5/50.0

Oraganic

Materials

Pallets

Batteries

30.0/22.2

Motor Oil

10.0/5.6

Soft bound

books

5.0/11.1

White Paper

50.0/94.4

Paper borad

2.5/0.0

Mixed Paper

45.0/94.4

News Paper

62.5/55.6

Paper 100.0/100.0

Brown 17.5/27.8 Clear 20.0/38.9 Deposit 12.5/0.0 Non-Deposit 12.5/0.0

Glass 80.0/66.7 Plastics 100.0/83.3

Non-Fibers,

"Containers"

77.5/88.9

Self-Sorting 87.5/100.0 Pick-up 67.5/50.0 Processing Facility Drop-off 62.5/11.1

Tin/Aluminum 80.0/77.8

Notes: Values indicate percent understanding, reflected by scores of 3 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

Cardbord

Magazines

7.5/44.4

Shoes

5.0/11.1

Toner 2.5/16.7 Tires 15.0/0.0 Food Oil 2.5/0.0

Other

Fly Ash 0.0/0.0

Construction Waste 12.5/0.0

Paperboard

12.5/0.0

Mixed paper

50.0/100.0

News paper

97.5/94.4 Soft bound

books

25.0/27.8

Junk Mail

40.0/11.1

Paper 100.0/100.0

Phone Books 2.5/38.9

Loft Wood 7.5/0.0 Fluorescent 2.5/11.1

Fabric 15.0/5.6

Fibers 5.0/0.0

Careboard 85.0/55.6

White paper

95.0/100.0

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