Text Messaging and Camera Phones in the Classroom:
Resetting the Moral Compass or Generational Differences?

Amy Gentry
Ohio University

Judith Gentry
Judy Roobian-Mohr
Columbus State Community College

     This study will examine trends in text and picture messaging in secondary and higher education classrooms, and the effect of emerging cell phone technology on attitudes towards cheating. The present study had its inception in a student statistics and research project at Ohio University.  There, 100% of the Ohio University students sampled on cell phone use reported sending or receiving text messages during class (Gentry, 2005, 2006). The present study is devoted to taking a closer look at what students are texting while they are in class as it relates to their attitudes toward using cell phone technology to cheat. Strom & Strom (2007), in looking at high school students, set the stage for the present study when they wrote, “Emergence of technological devices has spawned new and more sophisticated approaches to deceptive conduct.” (p. 108). Today, the popular press, newspapers, and even the evening news have reported on the problem of cell phone use in the classroom. The question immediately arises, do classroom factors such as sanctions for using a cell phone in class or honor codes affect students’ attitudes toward using electronic gadgets to cheat or socialize in class?  There is no doubt the field of telecommunications is rapidly changing, and what may be state-of-the-art today is obsolete tomorrow.   Bohlin, Burgelman & Casal (2007) write, “Globally, wireless services, driven by cellular mobile, have advanced faster in the last 10 years than the whole of telecommunications technology over the past 100 years.” (p. 161) Nowhere is the sting of these rapid changes felt as strongly as in high school and college classrooms.  A stroll on any college campus finds nine out of ten students talking on cell phones, text messaging (TM) or gathered in groups laughing at a picture or short video on a camera phone.  Often similar scenes are found inside the classroom as well. 
     Ling and Baron (2007) note that because educators in the United States have for over a decade encouraged middle school students to use computers for writing papers, “College freshmen arrive as proficient typists” (p. 293) and already trained in the use of abbreviations and lexicons needed to TM.  A recent study by Leung (2007) looks at the reasons why college students in Hong Kong use text messaging or short message services (SMS) on cell phones.  Leung’s (2007) research concluded that text messaging is especially popular with college students for “convenience, its low cost, and its utility for coordinating events” (p. 115). It also found gender differences in usage patterns, with male students from high-income families the more likely users of SMS.  Similarly, Aoki and Downes (2003), near the beginning of the TM and picture messaging revolution, noted that cell phones were “blurring the boundary between work and private life and public and private space” (p. 352).  With this blurring, social activities such as calling a friend take place in public, such as a classroom or restaurant, often to the amusement of onlookers. Aoki and Downes (2003) also suggested that cell phones add a feeling of safety for college students, with many responding positively to statements about feeling lost when phones are turned off or misplaced. Today’s cell phones receive and store text messages when they are turned off, a feature not available just a few years ago. 
     According to Leung (2007), other findings were that intrinsic psychological factors contribute to SMS use.  Two intrinsic reasons were the need to show affection by using SMS “to let others know I care about their feelings” (p. 122) and to escape from what the individual should be doing.  Similarly, a study done in the Netherlands by Peters and ben Allouch (2005) listed uses of the personal digital assistant (PDA) in both work and personal contexts, to include “…during boring moments or moments of waiting, during public transportation or spending spare time…” (p. 251).  In Finland and the United Kingdom, Faulkner and Culwin (2005) found that school age girls were more likely to have their cell phones on all the time, and to use TM and picture messaging as a social activity.  Revealing the rapid changes in the cell and camera phone markets, they found females averaged only 6.3 messages per day while males averaged 4.8. Just three years later, most teens have unlimited TM capabilities contributing to an exponential growth in use of this communication medium.  Faulkner and Culwin (2005) suggested that gender differences emerge quite early and are maintained into adulthood. However, neither they nor Leung (2007) specifically addressed the use of mobile phone technology in the classroom.
     A current study on college cheating by Vandehey, Diekhoff and LaBeff  (2007), is an extensive literature review and found rates of cheating ranging from 52% to 90%, but noted that inconsistencies in how cheating is defined posed problems in comparing results from one study to the next.  Proposing that cheaters were using the Freudian defense mechanism of rationalization, they concluded that cheaters tended to agree more with statements such as “Jack should not be blamed for cheating if. . .”

• “the instructor doesn’t seem to care…”
• “everyone else in the room seems to be doing it”
• “the instructor left the room” , or if the
• “the course is required.” (p. 473).  

     Vandehey et al. (2007), did not, however, address using cell phones to cheat.  Their study identified nearly twenty variables where cheaters and non-cheaters significantly differed, but did not cite gender differences.
     In 1999, before the cell phone and TM explosion, Whitley did a meta-analysis of gender differences in cheating attitudes and behavior, and concluded that gender was an important factor in both cheating behaviors and attitudes towards cheating. Males had slightly more positive attitudes and behaviors towards cheating, even though earlier studies on cheating seem to ignore gender differences. When looking at ethical behaviors from a psychological perspective, Ercegovac and Richardson (2004) concluded that Piaget’s and Kohlberg’s works provide an excellent theoretical structure for observable changes in ethical behaviors in the academic arena.  They found that other variables that distinguished cheaters from non-cheaters (p = .001) were age (younger students) and noticing others cheating or thinking that the majority of students approved of cheating. They did not discuss the role that cell phones or TM could play in cheating. Vandehey et al. (2007), found that a “credible threat of punishment appeared to be the best deterrent to academic dishonesty.” (p. 477) As educators have looked at self-reports of cheating, Kidwell, Wozniak and Laurel (2003) listed seventeen different behaviors in their survey of college students, again not including the use of TM or cell phones.  Interestingly, they found that faculty perception of cheating using technology (Internet term papers) was greater than the student reports of these actions. However, by 2008, there was at least one paper-selling website (OPPapers.com) listing 58 different papers available under the search terms <Using Technology Cheat>.  Jensen, Arnett, Feldman and Caufman et al. in 2002 addressed the question of why students cheat, including gender variables, and found “cheating behavior was more common among those who evaluated cheating leniently, among male students and among high schoolers” (p. 209). 
     McMahon (2007) notes, “Not only is cheating on the rise nationally…but there has also been a cultural shift in who cheats and why.” (p. 1).  In U.S News & World Report Archive, Kleiner and Lord (1999), in a survey done almost ten years ago, reported that “84% of college students believe they need to cheat to get ahead in the world… 90% of college students say cheaters never pay the price… 90% say when people see someone cheating, they don’t turn him in.”  This survey was conducted before the TM and picture messaging boom. McMahon (2007) suggested it is the students who have the most to lose (in high school), such as Advanced Placement (AP) students, who are more likely to cheat and also that there is a 99% chance of not getting caught.  Not surprisingly, one of the five recommended ways to curb cheating is to “ban electronic devices in testing rooms” (p. 8).
     In 2003, Popyack, Herrmann, Zoski, Char and Lass elaborated on the many avenues students have for using high-tech devices to cheat, and noted that TM provides an opportunity for students to electronically leave the classroom during a test to get answers.  Using state-of-the-art technology to cheat seems to be a part of the student-teacher dynamic. For example, the use of programmable gadgets to cheat in class was reported by Schab (1991) who looked at the likelihood math and science students were using calculators to retrieve information during tests.  They found nearly 100% of respondents on the wrong side of the ethical divide. Fifteen years later the news was abuzz about the new Mosquitone, a ring tone that, in theory, only children, high schoolers and young adults can hear (Vitello, 2006).  
     As far as the consequences of cheating, Vandehey et al. (2007) suggest that honor codes may help deflect the us-versus-them mentality found in some academic environments.  However, according to the popular press, educators are imposing severe sanctions, ranging from banning cells phones to insisting they be turned off and stowed in students’ book bags (Meyers, 2008).   Issues of cheating aside, phones on vibrate do distract students during class.  As economists and professors in the business area look at business ethics and academic dishonesty, Read (2004) cites the use of internet-enabled cell phones by a group of accounting students to cheat on their final exam. Grimes and Rezek (2005) and Callahan (2006) are among those suggesting students may be doing informal cost-benefit analyses, which lead to a green light for cheating. The potential gains can be huge while the likelihood of being caught and punished is perceived as miniscule. In particular, the social acceptability of cheating, lax classroom situations and uninvolved teachers seem to lower the likelihood of getting caught and being penalized.
     The purpose of this study is to examine current trends in text and picture messaging in secondary and higher education classrooms.  The literature suggests that the cell phone user’s age and gender affect attitudes towards cheating, as well as attitudes towards using TM to socialize with friends during class. High schools and colleges have very different policies on cell phone use and sanctions for cheating, and the present study also investigates whether this affects students’ attitudes.  Anecdotal evidence and the popular press suggest students are spending class time on TM often at the expense of what they should be learning.  How students perceive the trade-off between texting in class versus paying attention to what their teachers are doing raises the issue of opportunity cost or the student’s cost-benefit conclusions. Recent advances to include the camera phone, Internet capability and unlimited text messaging all make it easier for students to use cell phones to unobtrusively cheat on a test or to technologically leave the room and visit, unnoticed, with friends.
Method
Participants
     The present study surveyed three types of students, high school, traditional community college and university, and non-traditional (older) college from community college night classes, as presented in Table 1.
     The suburban public high school and community college are located in a large Mid-western city and the university is located in a rural area of the same region. Subject selection used samples of convenience, but given the diversity of settings is thought to be representative.  At the community college, students completed the survey in day and evening sections of psychology and economics classes and the university students were from a variety of psychology classes. Table 2 is a breakdown by gender, with approximately equal numbers of males and females.
Materials
     The Cell Phones in the Classroom survey reminded students that the survey was confidential, and contained a 24-item Likert scale of attitudes towards cell phone use and cheating, with 1=Disagree and 5=Agree.  Consent and assent forms (for high school students) were attached as a cover page. Demographic data included gender, age, whether or not they owned a cell phone, length of ownership, and who pays for the cell phone.  Other demographic data collected were on cell phone features and usage. They included whether the student’s phone had a camera and text messaging capability, and whether the student had ever sent or received a text message while in class.
Procedure
     When distributing the survey in college classes, the researchers (not the students’ regular teachers/professors) explained the consent form before handing out the survey to the class. Given the nature of the questions on cheating, students were reminded that their responses were confidential.  Participants were asked to sign the consent form and detach it from the survey.  Signed consent forms and completed surveys were collected separately at the end of the survey process.  Of the 118 surveys handed out in the community college only two students declined to complete the survey, with similar results at the university.
     At the high school there was a different process because students were under the age of 18 and parental consent was necessary.  On the first day, 130 students were each given a parental consent form in neon green.  Again, the purpose of the research was explained and students were given two days to have forms signed and returned to the school guidance counselor.  On the second visit the researcher handed out the Cell Phones in the Classroom survey to those students who had parental consent forms on file. At the high school’s request, students completed the survey during study halls.  Again, the confidentiality was explained and it was stressed that no high school personnel would know what any individual had answered on the survey.
Results
     A between subjects ANOVA reveals significant effect of student type [F(2,261) = 35.292, p<.001] and no main effect of gender or an interaction between gender and student type [p>.05].  Table 3 presents the data for significant responses by student type.  To explore this student type effect, post hoc analyses were conducted looking at student type for each question. Significant gender differences [p < .05] are shown in Table 3.
     There was no significant difference in gender but with the prior hypothesis regarding the role of gender, the present analysis also looked at individual survey items where significant differences were found looking at student type and gender [p<.05] as shown in Table 4.
Discussion
Effects of Student Type
     Data analysis indicated that there were significant differences based on student type (Table 3). For each of these questions, high school students’ responses were significantly higher on average compared with both traditional and nontraditional college students.  There were no differences between traditional and nontraditional college students. Findings for individual questions are discussed below.
Attitudes towards cheating with cell phones (Q14, 15, 19, 22, 23)
     While all three respondent groups disagree with these statements, high school students respond more positively compared to both tradition and nontraditional students (see Table 3). High school students are more likely to believe it is okay to text a friend for an answer, text others if a teacher leaves a room and cheat because others cheat. That high school students are more likely to text each other for help on a test is consistent with McMahon’s (2007) findings and suggests that younger students are blurring the line between cheating and “collaborating.” This supports Aoki and Downes’ (2003) observation that cell phone use diminishes boundaries. With K-12 education moving toward more group work and activities, some students may find it easy to rationalize the extension of collaborative learning into the testing process. Leung (2007) also noted that students valued the convenience of text messaging, and what could be more convenient than to be able to receive real-time help from a colleague when stumped by a test question? For all students, texting when the teacher is away and students are less apt to be observed and penalized likely reflects the results of an intuitive cost-benefit analysis. This is in agreement with the conclusions of Grimes and Rezek (2005) and of Callahan (2006), who pointed to lax classroom monitoring and uninvolved teachers as contributing to cheating behavior. That students view cheating as a crime of opportunity can be seen in their responses to Question 24, “I would be more tempted to use my cell phone to cheat in a large lecture class.” It is interesting that the surveyed group of high school students, who do not have large lecture classes, responded most positively here, while college students, traditional and nontraditional, disagreed more. It seems likely all three student types are equating a large lecture hall with lax supervision and low teacher involvement in the testing process. If their perceptions are correct, the likelihood of getting caught cheating and being penalized decreases, making these responses is consistent with those given on Q15.
Penalties(Q11)
     While all respondent groups generally disagreed with this statement, high school students did so less strongly (2.967), followed by traditional college students (2.01) and nontraditional college students (1.787), with no significant difference across college groups. This likely reflects the disparity in sanctions applied at the secondary level as opposed to those imposed in a college setting. Many high schools, including the one in this study, confiscate the offending student’s phone and require a parent to come to the school to retrieve it. Some also serve up a stint in detention. Other high schools have even stiffer penalties for second and third offenses. Post-secondary students who get caught using cell phones in class to text socially tend to be verbally admonished or have their phones collected, but usually only until the end of that class period. Thus, the potential costs in a high school student’s cost-benefit consideration weigh more heavily than they would for college students where there is no parental involvement and separation from one’s phone is brief. This jibes with the findings of both Vandehey et. al. (2007) and McMahon (2007) that cheating behavior and perceived sanctions are inversely related.
Cheating behaviors and Peer Influence (Q19, 22, 23)
     These bring together the interaction between peer group identification and a student’s individual moral compass. Although all three groups of students provided responses at the low (disagree) end of the scale, there is a significant difference between high school and college responses in each case, with high school students registering means above those of college students. Vandehey et. al (2007) found cheaters to be in high school, more likely to agree that “everyone else in the room seems to be doing it,” to have observed others cheating or believing other students thought cheating was okay. This study’s findings are consistent with those results. On all three questions, high school students posted higher mean scores than did their college counterparts.  It may be students are becoming more ethical with age and as they proceed in their academic careers, or peer behavior may be less influential as students mature. For whatever reason, there is visible and significant attitude change as students become more mature. For some high school students the pressure to earn grades and get into a prestigious college may be affecting their cheating behavior and attitudes.
Social Uses (Q20)
     The high school students’ relatively high mean of 2.667 can be interpreted several ways. On the one hand, it seems to support the Aoki and Downes (2003) finding that functional boundary lines are blurring. If “during a test…” was read to mean while the testing period is still in progress, high school students may believe the test is finished when they are done with it rather than when they have been dismissed and left the testing site. Peters and ben Allouch (2005) found PDAs were used during boring moments or when individuals were forced to wait around, and certainly having to sit idly by while others finish an exam would be tedious. On the other hand, if respondents read the question to mean it is okay to use a cell phone even while they are still taking an exam, then the boundary blurring is even more pronounced. Much has been made of multi-tasking in today’s busy world and this may be a case in point. Alternately, it could signal an inability to focus on the task at hand. Using their cell phones to reach out to each other is in step with Leung’s (2007) finding that students turn to cell phone exchanges to provide each other moral support.
     When asked about large lecture halls (Q24), again males disagreed significantly less with the statement than females. Consistent with the literature on cheating, Whitley and Whitley (1999) reported that males were more likely to cheat and have more positive attitudes towards cheating than females. This may be due to a tendency to be less risk-averse or it may reflect the result the result of a quick cost-benefit analysis that concludes the likely cost of cheating is minimal in this setting. On Q15, males again significantly disagreed less with the statement on text messaging (TM) friends during a test for help than  did females. Males are significantly more likely to believe that teachers do not notice when students are texting in class. On the other hand, females are significantly more likely to enjoy texting and are more likely to feel uneasy when they do not have their cell phones nearby (4.136 on a 5 point scale).
Teachers noticing Text Messaging(TM) (Q10)
     High school students had the highest values (3.3), followed by traditional college students (2.258) and nontraditional college students (2.064). This indirectly supports Ling and Baron’s (2007) observation that secondary students develop keyboard skills and acquire TM vernacular early on. These younger students, who probably cannot recall life without their cell phones, are also apt to be more adept at surreptitious texting. Technological developments such as the Mosquitone ring tone (Vitello, 2006) capitalize on younger students’ physiological advantages over their teachers when it comes to recognizing the call of a cell phone, bolstering students’ “Teachers don’t notice…” position.
Effects of Gender
     Based on literature we had specific hypotheses regarding gender effects for questions associated with risk taking and penalties. We anticipated that males would agree more with statements on risky behaviors involving using cells phones to cheat. Secondly, we believed that females would be more sensitive to statements on penalties for cheating. In Table 4 it can be seen that there are significant differences in attitudes based on gender. Clear classroom policies on cheating may deter females from using their cell phones and TM to cheat. There is also a significant difference between males and females using TM in classroom environments. Males responded more positively to text messaging (TM) a friend during a test to make plans later on, a risky behavior, since sanctions could be severe if caught.
Conclusion
     The present study did find significant differences between college and high school students regarding their attitudes towards using cell phone technology to cheat on tests.  Secondary students are still developing moral compasses that point away from academic dishonesty and are taking their misdirected world views to college.  The trends identified in the cheating and cell phone literature were also found in this study, with younger, male students having more positive attitudes towards cheating and being more likely to use cell phones in general.  Female students appear to be more deterred when there are severe and public sanctions for using cell phones.  Female high school students reported being more anxious when cell phones were turned off, and were more likely than males to find TM enjoyable.  An emerging body of literature on cell phone technology suggests there are many characteristics of an educational environment that foster and support the blurring of social boundaries and so can lead to inappropriate cell phone use.  Reasons for using cell phones during class include boredom, mandatory attendance, or a perceived notion that teachers don’t know or care if students are texting and/or cheating. Economists might describe this as a poorly conceived cost-benefit analysis and/or being so “in the moment” as to ignore the opportunity cost of inattentiveness in the classroom.
     Further study into the attitudes of teachers and professors is needed.  While we have looked at the use of TM and cell phone technology in student attitudes, researchers are only beginning to look at the effects of honor codes, for example, on using cell phones to cheat on exams.  In a world where it is the very young who are the most “tech savvy”, the student becomes the teacher.

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