See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/316599851 Factors affecting academic reading among students Conference Paper · November 2015 CITATIONS READS 0 4,653 Some of the authors of this publication are also working on these related projects: change management View project All content following this page was uploaded by Maria Cecilia Eijansantos- Remanente on 01 May 2017. The user has requested enhancement of the downloaded file. FACTORS AFFECTING THE ACADEMIC READING HABITS OF HOSPITALITY MANAGEMENT STUDENTS Maria Cecilia Eijansantos-Remanente ABSTRACT The reading habits and interests of 95 hospitality management students were examined, with amount of time spent reading materials related to their courses and time spent reading different content as proxies for measuring reading habits and reading interests, respectively. Mann-Whitney tests showed that the differences in the responses of males and females in terms of reading habits, perceptions of the benefits of reading, and the encouragement they receive from family and peers were not significant. Online materials were preferred over print materials. Male students generally spend more time reading print and online news articles than female students, and this finding is significant at a 95% confidence level. Bivariate associations between academic reading and factors affecting reading habits were tested using Spearman rank correlation. Among the factors tested, the students’ perception that reading improves one’s grades and their having close friends in school were negatively correlated with the amount of time they spend in academic reading. Although these correlations were all weak and not significant, the results still suggest that not all students study merely for the grade and that they tend to assess their peer’s propensity to read relative to their own. Ordinal regression of these factors showed that having parents and siblings who encourage one to read and having close friends in school who regularly read have significant contributions to predicting the amount of time that students spend in academic reading, implying the importance of social relationships in motivating the youth. KEYWORDS: academic reading, reading habits, reading interests, hospitality management students INTRODUCTION Reading is an essential life skill as it not only “increase(s) knowledge but also builds maturity and character, sharpens thinking, and widens awareness in social, economic, political, and environmental issues” (Abidin, Pour-Mohammadi, & Jesmin, 2011). Reading is particularly important among ESL students or those for whom English is a second language (Le Thanh, 2010; Constantino, as cited in Kelly & Kneipp, 2009). A skilled reader has strong comprehension of printed text (Anonat, 2011) owing to a strong vocabulary developed from earlier years of reading. However, despite the many benefits of reading, not many regularly read for either leisure or academic purposes. College is seen as the last stage of formal education for many individuals (Lemanski, 2011, citing the 1994 study by Brown and Knight), and thus, the responsibility of training students to become independent and lifelong learners rests on college institutions. As an educator, this researcher has observed that students appear to rely only on their lecture notes and hardly refer to textbooks and prescribed reading lists. Such reluctance to read could explain students’ difficulty in engaging in meaningful classroom discussion, as they prefer to listen passively to their teachers. Their written submissions lack insight and, at times, closely resemble material found online. Bilbao et al., (2008) describe learning as “a social process where interactions with other learners and the teacher” are needed. Inside the classroom, students can maximize their learning by actively sharing their ideas, and reading materials can be an ideal source of such ideas for sharing. 1|Page Previous studies that examined the effect of different demographic variables on frequency of reading yielded conflicting findings. Summers (2013) reported that males preferred online materials on “informational topics, hobbies, and careers” whereas women chose online materials on “parenting, crafting, family life, celebrity gossip, shopping, and cooking.” In Johnsson-Smaragdi and Jo¨nsson (2006), social background notwithstanding, girls were found to be more avid readers than men were. By contrast, no remarkable difference was found in the amount of time that female and male college students in Taiwan spent on extracurricular reading (Su-Yen Chen, 2007); the study concluded by suggesting the active role played by cross-cultural differences in shaping college students’ reading interests and habits. A report by Dana Gioia (2004), Chairman of the US National Endowment for the Arts, showed that literary reading has declined among Americans across age and educational levels. Furthermore, people tended to read less frequently as they grew older. Scales and Rhee (2001) proved that race and education were strong predictors of reading habits: White Americans were more inclined to reading than their Asian counterparts, whereas graduatelevel respondents read more often than those who attained lower education. In the study by Su-Yen Chen (2007), students majoring in arts and architecture were found to spend the largest amount of time in reading than students of other majors. Lemanski (2011) showed that access to reading materials and reading assessment were main factors affecting undergraduate students’ inclination to read. He examined student attitudes toward several teacher strategies: administering random tests and Q&As during lectures, requiring the submission of reading summaries, posting all the readings online, photocopying all readings in one pack, limiting textbooks/references to 2 to 3, and providing discussion questions as a guide. Of these strategies, access to online readings (96%) and submission of reading summaries (76%) were most favored by majority of the students. Some students believed that assessment strategies like quizzes and Q&As only promote surface learning (e.g., memorization of facts) whereas receiving a set of photocopied readings “spoon fed” learners, thus defeating the purpose of encouraging independent study. In the USA, the Sustained Silent Reading Handbook by Pilgreen (as cited in Lee, 2011), which was published in 2000, discussed access to reading materials, appeal to learners, an environment conducive to reading, encouragement, training for reading coaches, and devoting time to reading as among the factors common to effective silent reading programs. Online resources are also an effective tool for increasing independent reading (Abidin et al. 2011; Grimshaw, S., Dungworth, N., & Morris, A., 2007). Abidin et al. (2011) showed that more than half of their group of young respondents spent one to three hours on the Internet, although a substantial amount of this time was spent reading emails, movie reviews, and comic strips. More than a third rarely read online magazines, online news, and online e-books. A related study by Grimshaw et al. (2007) showed no significant differences in young children’s comprehension when reading e-books than when reading printed text, yet the narration, animated pictures and sound effects, and access to an online dictionary available when reading e-books enhanced the children’s enjoyment of reading. Individuals can be trained and encouraged to become avid readers. Motivation to read is a predictor of reading success (Manning, Aliefendic, Chiarelli, Haas, and Williams, 2011-2012). Anonat (2011) terms the “exposure to literacy artifacts and events” as “literacy socialization.” She suggests three stages of reading literacy: emergent reading is when individuals recognize and interpret symbols and pictures, the beginners’ stage is when readers gain the confidence to read, and finally, the skilled readers’ stage is when individuals can read fast or grasp ideas simply by skimming. Additionally, she cites three factors influencing reading comprehension: the reader’s background knowledge, the authors’ presentation of ideas, and the reader’s intention for reading or “purpose.” 2|Page Johnsson-Smaragdi and Jo¨nsson (2006) best summarized the many benefits of reading: Reading is also supposed to enhance the communication potential by developing our language and vocabulary, by affecting the ability of logical reasoning, the capacity of expressing oneself and by affecting the level of comprehension and understanding. Other arguments, that may concern the cognitive as well as the emotional realm, are that reading stimulates the imagination, creates images in the mind and gives the power of insight. Further arguments along these lines are that reading may enhance emotional intelligence, evoke empathy and provide characters for identification. Practical reasons that speak in favour of reading mainly pertain to the area of worklife and studies and also to the ability to act as a citizen in the democratic process. These reasons underscore the importance of understanding texts and the ability to produce texts, and the ability to formulate arguments in discussions. The present study focuses on independent reading among college students, or reading without being prompted to do so, as one recognizes its many benefits. Correlations between gender and reading habits, perception of the benefits of reading, and parental and peer influence were likewise tested. RESEARCH METHODS First, students’ reading habits and interests were examined vis-à-vis their gender. Their reading habits and interests were measured in terms of the amount of time they spend in reading, their usual sources of reading materials, and their preferred reading content. Second, correlations were measured between the amount of time that students spend in academic reading and different factors: school requirements such as quizzes and class recitation; parents, siblings, and peers who influence one to read; having an environment at home that is conducive to study; and the perceived benefits of reading (i.e., better grades, wider vocabulary, keeping abreast with current issues). Finally, ordinal regression was run to examine the contributions of these factors, relative to each other, in predicting the amount of time that students spend in academic reading. 1. How much time do male and female students spend reading materials related and nonrelated to their schoolwork? 2. How often do these students read different types of content (academic, literary, self-help or inspirational, news, and entertainment) during school season? 3. What are these students’ common sources of reading material: bookstores, libraries, friends, or the Internet? 4. What are the perceptions of male and female students with regard to school-related reading, reading influences, and the benefits of reading? 5. Is there a relationship between the amount of time that students spend in academic reading (ACAD_READING) and each of the variables below? Schoolwork-related Searching for materials in reading lists (READING_LIST) Reading in preparation for class discussion (CLASS_DISCUSSION) Reading in preparation for quizzes/exams (QUIZZES_EXAMS) Reading influences Parents and siblings (FAMILY) Peers (PEERS) 3|Page Home environment (HOME_ENVIRONMENT) Benefits of reading Improved vocabulary (VOCABULARY) Updated with current issues (CURRENT_ISSUES) Higher grades in school (GRADES) 6. Are the variables READING_LIST, CLASS_DISCUSSION, QUIZZES_EXAMS, FAMILY, PEERS, HOME_ENVIRONMENT, VOCABULARY, CURRENT_ISSUES, and GRADES significant in predicting ACAD_READING? In answering the research questions above, the following null hypotheses were tested: H01a: There is no significant difference in the amount of time that male and female students spend in reading materials related and nonrelated to their schoolwork. (Question #1) H01b: There is no significant difference in the preferred reading content of male and female students. (Question #2) H01c: There is no significant difference in the perceptions of male and female students with regard to school-related reading, reading influences, and the benefits of reading. (Question #4) H02a: H02b: H02c: There is no correlation between ACAD_READING and school requirements. (Question #5) There is no correlation between ACAD_READING and reading influences. (Question #5) There is no correlation between ACAD_READING and the perceived benefits of reading. (Question #5) H03: READING_LIST = CLASS_DISCUSSION = QUIZZES_EXAMS = FAMILY = PEERS = HOME_ENVIRONMENT = VOCABULARY = CURRENT ISSUES = GRADES = 0 (Question #6) The survey period was from September 9 to 25. Random sampling was conducted, and 99 hospitality management students served as respondents, representing 16.5% of the target population (confidence level: 95%, margin of error: +9). Questionnaires that were incompletely filled were discarded, leaving only 95 usable forms or a response rate of 95.9%. A three-part questionnaire was used. Part A assesses students’ reading habits, that is, how much time they spend reading materials related and nonrelated to their schoolwork and their common sources of reading materials (bookstores, libraries, friends, or the Internet). Part B assesses students’ reading interests using a Likert scale, that is, how often (Always, Often, Sometimes, Rarely, or Never) they read different types of content (academic, literary, self-help, news, and entertainment) during and outside school season. In part C, students are asked to indicate whether they considered a set of statements to be Always, Often, Sometimes, Rarely, or Never true. These statements are designed to assess students’ academic reading habits, perception of the benefits of reading, and the influences they receive from family, peers, and their home environment. Statement# 4 was added to examine students’ preference for print over online reading materials. In developing the questionnaire, the researcher referred to Lemanski (2011), Abidin et al. (2011), Scales and Rhee (2001), and Chen (2007). The scale for measuring the factors affecting reading habits (questions 1-3, 5-10) used in the present study has a high level of internal consistency, as indicated by the Cronbach’s alpha of 0.783. Mann-Whitney test was used in analyzing the differences in the responses of two independent, categorical groups, i.e., male and female, with regard to time spent in academic reading and reading interests. 4|Page Spearman’s rank correlation coefficients were calculated to determine the significance of the associations between time spent in academic reading and student perceptions of school-related reading, the benefits of reading, and the influences they receive from family and peers. As the correlations between variables were mostly not statistically significant, which is further discussed in the next section, ordinal regression was conducted to determine whether the study variables, relative to each other, are significant in predicting the amount of time that students spend in reading materials related to their schoolwork. RESULTS Students’ reading habits and interests were measured as (a) the amount of time spent in reading materials related and non-related to schoolwork and (b) the amount of time spent in reading different types of content: academic, literary, self-help, news, and entertainment. Other factors affecting students’ propensity to read were also reported: their source of reading materials; their perception of the benefits of reading; family and peers influencing them to read; and having an environment conducive to reading. 1. How much time do students spend reading materials related and nonrelated to their schoolwork? As shown in Figure 1, majority of the male (64.5%) and female (68.8%) students engaged in schoolrelated reading less than five hours each week. Nearly a third (31%) of the respondents spent more than five hours each week reading; the percentage is slightly lower (26%) for reading materials not related to schoolwork. Only one respondent, a female student, read at least 24 hours a week for her studies but a few female students reported spending close to 24 hours each week reading materials non-related to their studies. 5|Page Figure 1. Time spent in reading materials (a) related to schoolwork and (b) not related to schoolwork Levels of significance were obtained using SPSS 22.0. The differences in academic reading (U = 909.5, p =.497) and in reading materials non-related to schoolwork (U = 844.5, p =.226) between males and females were not statistically significant at α =.05. Therefore, H01a could not be rejected. 2. How often do students read different types of content (academic, literary, self-help or inspirational, news, and entertainment) during school season? Tables 1 and 2 show how often students read different types of content, in both print and electronic format. Entertainment articles, both in print and electronic format, were popular among the students (35% and 38%, respectively). Male students read printed and electronic news articles more often than female students did. Literary pieces such as novels were the least preferred by males. The percentage of students who always or often read different types of content online was generally higher than for print materials: 44%, 52%, 48%, 52%, and 70% versus 40%, 47%, 45%, 40%, and 66% for academic, literary, self-help, news, and entertainment materials online and in print, respectively. Table 1. Frequency of reading different types of content (in print) 6|Page Table 2. Frequency of reading different types of content (online) Test Statisticsa Acad_print Mann-Whitney U Wilcoxon W Literary_ Selfhelp_ News_ Entertainment print print Print _print Acad_online Literary_ Selfhelp_ News_ Entertainment online online online _online 859.000 779.500 927.500 726.000 880.000 988.000 886.500 877.500 783.500 978.000 1355.000 1275.500 3007.500 2806.000 2960.000 3068.000 1382.500 2957.500 2863.500 3058.000 -1.126 -1.751 -.543 -2.194 -.930 -.034 -.876 -.950 -1.712 -.117 .260 .080 .587 .028 .353 .973 .381 .342 .087 .907 Z Asymp. Sig. (2tailed) a. Grouping Variable: Sex Figure 2. SPSS Output showing Mann-Whitney U values and their significance All asymptotic p values for different types of content, except for printed news articles (U = 726, p = .028) were less than α = 0.05, as shown in Figure 2. Thus, there are no significant differences in male and female students’ preferences for different types of content except for printed news articles, and the null hypothesis H01b cannot be fully rejected. Majority or 33% of the respondents considered the statement “I prefer print over online reading materials” to be sometimes true, but a considerable percentage—25% and 27% of them—viewed the statement to be always and often true, respectively (see Table 3). The distribution of responses differed between males and females, yet these differences are not statistically significant (U = 865, p = .295) at a confidence level of α = .05. The nonsignificance of findings after using a Mann-Whitney test indicates that the nominal characteristic of the sample does not make a statistically significant 7|Page difference on the variable measured (Cohen et al., 2011), that is, being male or female made no difference on the reported reading habits and interests of the respondents. Table 3. Male and female students’ preference for print over online materials 3. What are the students’ common sources of reading material: bookstores, libraries, friends, or the Internet? Fig. 3a 8|Page Fig. 3b Fig. 3c Fig. 3d Fig.3. Common sources of reading materials of male and female students: (a) bookstores, (b) libraries, (c) friends), and (d) the Internet Majority of the respondents downloaded from the Internet or borrowed materials from friends for their schoolwork. Borrowing from libraries and buying from bookstores were ranked as third and fourth, respectively, most common ways of obtaining reading materials for schoolwork. 4. What are the perceptions of male and female students with regard to school-related reading, reading influences, and the benefits of reading? 9|Page As shown in Table 4, majority of both female and male students (41% and 45%, respectively) only sometimes search for the textbooks prescribed by their instructors, but frequency of searching for textbooks is still higher among females than males (28% versus 13%, respectively). By contrast, the percentage of students who “always” and “often” read in preparation for class discussion is higher in males than in females (19% and 26%, respectively, for males, and 13% and 19%, respectively, for females). More female than male respondents rarely read books when reviewing for quizzes and periodical exams. 10 | P a g e Table 5 shows students’ perceptions of the benefits of reading. Table 6 shows their reaction to the statements “My parents and siblings influence me to read,” “I have close friends in school who read,” and “There is a quiet area at home where I can read.” As shown in Table 6, 64% of the males and 53% of the females disclosed that their parents and siblings always and often encouraged them to read. Furthermore, 68% of the males and 52% of the females said that they have close friends in school who regularly read. The higher percentages for male students imply that they receive more encouragement to read from family and peers than the female students. Conversely, more females (64%) than males (55%) reported that they always and often have a quiet place at home that is conducive to study. However, the results of the Mann-Whitney test (Figure 4) show that the differences in the perceptions of male and female students with regard to schoolwork-related reading, the benefits of reading, and influences from family and peers are not statistically significant at α = 0.05: READING_LIST U = 940, p = 0.663; CLASS DISCUSSION U = 896, p = 0.401; QUIZZES_EXAMS U = 939.5, p = 0.664; VOCABULARY U = 858, p = 0.264; CURRENT_ISSUES U = 813, p = 0.139; GRADES U = 802.5, p = 0.111, FAMILY U = 914, p = 0.521; PEERS U = 869, p = 0.311; and HOME_ENVIRONMENT U = 859.9, p = 0.272. Asymptotic p values for these variables were all above .05 and thus, the null hypothesis H01c cannot be rejected. 11 | P a g e Figure 4. SPSS Output: Mann Whitney test on gender and factors affecting reading 5. Is the amount of time that male and female students spend in reading (ACAD_READING) related to schoolwork (READING_LIST, CLASS_DISCUSSION, QUIZZES_EXAMS), the benefits of reading (VOCABULARY, CURRENT_ISSUES, GRADES), and reading influences (FAMILY, PEERS, HOME_ENVIRONMENT)? Bivariate correlations were calculated using Spearman’s rho in SPSS 22.0. Table 7. Correlation with ACAD_reading Spearman's rho READING_LIST CLASS_DISCUSSION QUIZZES_EXAMS VOCABULARY CURRENT_ISSUES GRADES FAMILY PEERS HOME_ENVIRONMENT 0.038 0.092 0.155 0.089 0.047 -.005 0.077 -.109 0.146 Sig (2-tailed) 0.718 0.375 0.134 0.392 0.652 0.962 0.459 0.293 0.159 As shown in Table 7 above, having peers or close friends in school who regularly read is negatively correlated with academic reading. This negative correlation implies that students who do not read much perceive that their peers read “often.” It could also mean that when a student reads often, he/she perceives that his/her peers in school do not read very often, indicating a tendency to assess other individuals’ frequency of reading relative to one’s own. Similarly, the perception that reading results in higher grades is negatively correlated with time spent in academic reading. That is, students recognize that their grades would improve if they read yet they still do not spend much time reading materials related to their schoolwork. The rest of the variables (READING_LIST, CLASS_DISCUSSION, QUIZZES_EXAMS, VOCABULARY, CURRENT_ISSUES, GRADES, FAMILY, PEERS, and HOME_ENVIRONMENT) are positively correlated with time spent in academic reading. An increase in these variables corresponds to an increase in the time spent in academic reading. However, the correlations above are all very weak and almost negligible. These correlations are not statistically significant, as the correlation coefficients or rho are less than the critical value for n = 95, df = 93, at α = 0.05 level of 12 | P a g e confidence (see Appendix B). Table 7 also reports the ρ values obtained for these variables, which all exceed 0.05 and hence not significant. 6. Are the variables READING_LIST, CLASS_DISCUSSION, QUIZZES_EXAMS, VOCABULARY, CURRENT_ISSUES, GRADES, FAMILY, PEERS, and HOME_ENVIRONMENT significant in determining ACAD_READING? In Table 8, “estimate” refers to the likelihood of an event happening. The table shows a direct relationship between QUIZZES_EXAMS and ACAD_READING; the increasing estimates means that students who were more likely to read books when reviewing for quizzes and exams were also more likely to spend more time in reading. By contrast, an inverse relationship was observed between CURRENT_ISSUES and ACAD_READING, which means that students who perceived that reading makes one well-informed on current issues were more likely to spend less time in reading. However, both relationships are not statistically significant at α = 0.05. Of the variables included in the regression, only READING_LIST, FAMILY, and PEERS were shown to have statistically significant contributions to predicting ACAD_READING. QUIZZES_EXAMS was almost significant (p = 0.052). The Wald statistics can be an indicator of the relative weights of these variables in predicting time spent in reading; therefore, referring to reading lists contribute the most to predicting time spent in academic reading. Table 8. Parameter estimates Estimate Wald Sig. Time spent in academic reading 1 hour or less 1.5 to 3 hours 3.5 to 5 hours -3.126 -1.158 .289 10.425 1.634 .104 .001* .201 .747 READING_ LIST Never Rarely Sometimes Often Always -38.964 0.702 -0.641 -0.818 0a 210.908 0.329 0.868 1.439 . 0.000* 0.566 0.351 0.230 . CLASS_ DISCUSSION Never Rarely Sometimes Often Always -3.69 0.308 -0.878 -0.183 0a 1.417 0.037 1.304 0.047 . 0.234 0.848 0.253 0.828 . QUIZZES_ EXAMS Never Rarely Sometimes Often Always -4.359 -0.33 0.674 1.429 0a 3.767 0.146 0.859 3.176 . 0.052 0.703 0.354 0.075 . VOCABULARY Never Rarely Sometimes Often -25.965 0.835 -1.488 0.152 0 0.247 2.677 0.042 0.997 0.619 0.102 0.839 13 | P a g e Always 0a . . CURRENT_ ISSUES Never Rarely Sometimes Often Always 47.855 -0.517 -0.616 -1.096 0a 0 0.168 0.493 2.196 . 0.996 0.682 0.482 0.138 . GRADES Never Rarely Sometimes Often Always 6.684 41.144 0.584 0.34 0a . . 0.518 0.219 . 1.000 1.000 0.472 0.640 . FAMILY Never Rarely Sometimes Often Always -2.166 -0.404 -1.526 -0.039 0a 1.445 0.181 4.522 0.004 . 0.229 0.670 0.033* 0.947 . PEERS Never Rarely Sometimes Often Always -0.639 1.917 1.828 1.319 0a 0.083 3.843 4.878 3.553 . 0.773 0.050* 0.027* 0.059 . HOME_ ENVIRONMENT Never Rarely Sometimes Often Always 3.021 -2.519 -0.525 -0.284 0a 1.102 3.292 0.571 0.19 . 0.294 0.070 0.450 0.663 . *Statistically significant at α = 0.05 Pearson Deviance Chi-Square Df Sig. 269.233 234 .057 195.118 234 .970 Figure 5. SPSS Output on goodness of fit In Figure 5, the Pearson (χ2 269.233, p = 0.057) and Deviance (χ2 = 195.118, p = 0.970) statistics (df = 234, p = 0.057) indicate that the model is a good fit to the data. Unlike most statistics wherein values lower than α are considered significant, in measuring goodness of fit, p values above 0.05 indicate goodness of fit because the assumption is that the model is a poor fit compared with the ideal model, i.e., one that perfectly fits the data. Model fit can also be measured by reporting the difference between the intercept-only and the final model, as shown in Figure 6. This difference is χ2 = 52.579 (df = 36), which is significant (p = 0.037 < 0.05). Such significance means that the independent variables contribute significantly to predicting 14 | P a g e the amount of time that students spend in reading. A larger difference would mean that the independent variables are better at predicting time spent in academic reading (Ordinal regression). -2 Log Model Likelihood Chi-Square Df Sig. Intercept Only 252.432 Final 199.853 52.579 36 .037 Figure 6. SPSS Output showing Model Fit Information Ordinal regression requires an assumption of proportional odds, that is, the independent variables should have an identical effect at all levels or categories of the dependent variable (Ordinal regression). In this study, responses to the dependent variable (ACAD_READING) were grouped into four categories, namely, < 1, 1.5 to 3, 3.5 to 5, and > 5 hours. Three dichotomous dependent variables were created based on these categories: category 1 sets the value of “1” as < 1 hour of reading and “0” if otherwise; category 2 sets the value of “2” as < 1 and 1.5 to 3 hours, “0” if otherwise; and category “3” sets the value of “3” as “< 1, 1.5 to 3, and 3.5 to 5 hours, “0” if otherwise. Separate binomial logistic regressions were run for each of these categories; however, the results are not discussed in depth in this paper; only the variables that were found to be statistically significant are included in the analysis in Table 9. It would suffice to say that the assumption of proportional odds was not met, as shown by results of the Test of Parallel Lines (Figure 7) where χ2 103.297, p = 0.009 (at α = 0.05). In this table, the null hypothesis model assumes proportional odds whereas the general model does not. Model Null Hypothesis General Figure 7. Test of Parallel Linesa -2 Log Likelihood Chi-Square Df 199.853 96.556b 103.297c 72 Table 9. Results of binomial logistic regression B (parameter estimates) Categor Categor Categor y1 y2 y3 Sig. .009 Exp(B) (odds ratio, OR) Categor Categor Categor y1 y2 y3 READING_LIST(1) 43.304 18.756 11.216 6.4E+18 1.4E+08 QUIZZES_EXAMS(1) 1.555 23.934 25.832 4.735 2.528 -9.031 -11.734 1.167 -2.97 -2.618 4.587 -3.016 -2.212 12.534 0 0 2.48E+1 0 3.214 0.051 0.073 FAMILY(3) PEERS(2) PEERS(3) 74281.7 7 1.65E+1 1 98.223 0.049 0.11 In Table 9, the huge differences among the slopes of the variables for each level or category of the dependent variable were very apparent. Thus, earlier results showing their statistical significance should be viewed with caution. 15 | P a g e The null hypothesis H03 which is “READING_LIST = CLASS_DISCUSSION = QUIZZES_EXAMS = FAMILY = PEERS = HOME_ENVIRONMENT = VOCABULARY = CURRENT ISSUES = GRADES = 0” means that the removal of any of these variables will not significantly affect the prediction of the amount of time spent in academic reading. H03 cannot be rejected because these variables contribute to predicting the amount of time spent in reading. DISCUSSION In this study, the reading habits and interests (measured as time spent in reading and preferred reading content) of 95 hospitality management students were examined in relation to their gender. Differences between groups were measured using Mann-Whitney test. The differences in the amount of time that male and female students spent in reading materials related and nonrelated to their schoolwork were not statistically significant at a confidence level of α = 0.05. Likewise, except for news articles, no statistical significance was found in male and female students’ preferred reading content. Bivariate correlations were measured between time spent in academic reading and several factors: referring to reading lists, reading to prepare for examinations, reading to prepare for class discussion; perceptions of the benefits of reading, such as improved vocabulary, higher grades, and keeping abreast with current issues; receiving encouragement from parents and siblings, having close friends in school who regularly read, and having a quiet place at home that is conducive to reading. The Spearman rank-order correlation coefficients were all not significant at α = 0.05. These findings should be viewed with caution to avoid a Type 2 error or supporting the null hypothesis when it is in fact false (Cohen et al., 2011) and when the alternate hypothesis is of practical significance. “[A] non-significant p-value does not necessarily mean that there is no association; rather, the non-significant result could be due to a lack of power to detect an association” (Elite Research). Thus, replication of the present study is recommended. Ordinal regression was used to test the relative weights of the following factors in predicting time spent in academic reading: referring to reading lists, encouragement from family, and having close friends in school who read were shown to contribute significantly to predicting academic reading. Reading to prepare for quizzes and examinations was also considered significant, with its p value lying close to the α-level of significance. As the assumption of proportional odds was not met, an equation for predicting time spent in academic reading was not produced, but the slopes of these variables—computed using binomial logistic regression—were reported. A direct relationship was found between students’ referring to reading lists and the likelihood of their engaging in academic reading. Therefore, teachers should regularly provide students with reading lists that contain not only the textbooks, but also, other references, especially those found online because, as reported earlier, students refer to online sources more often than they refer to print materials. In cases where copies of a reference are limited or too costly to obtain, teachers should consider providing one copy for the class to reproduce. Giving students the original materials to be used as references for class discussion is preferred over providing them with lecture handouts or printouts of presentation slides used in class. Among younger students, devoting time to silent reading inside the classroom is another strategy that teachers can adopt; for more mature learners, a class period can be devoted to research or a library visit. Teachers can also help in checking the recency and relevance of the library collection. The school can support students by subscribing to online journals (e.g., EBSCOhost, Emerald) and magazines (e.g., National Geographic Traveler), particularly because students ranked the Internet as their top source of reading material (consistent with the findings of Lemanski, 2011). Some read-worthy 16 | P a g e references can be downloaded from the Internet at no cost, but students may need guidance on where to look. To encourage students to read on the course topics in advance, they can be asked to read an entire chapter, for example, and their instructors can give them a quiz at the start of the class or before discussion. Pre-, during, and post-reading strategies can motivate students to become active learners (Pardede, 2006). Among the pre-reading strategies that teachers can use are orienting students on what they are about to read, connecting prior lessons with the reading material, and providing guide questions for reflection. Post-reading activities include summaries, discussion, and reading logs. When asking students to write their reflection on a topic, a better alternative to assigning homework would be to allot 30 minutes of the class session to a writing activity to keep students from submitting plagiarized work. Students tend to read more often when they are encouraged by parents or siblings and when they see that their close friends in school read. This finding implies the importance of social relationships in motivating the youth. Teachers can initiate online forums where students can discuss their readings, and they can assign reading buddies. Libraries can draw inspiration from bookshop cafés such as those found in London, and consider offering café-like experiences for library users, without causing damage to their book collection. At home, quiet nooks can be designated as reading areas where students can engage either in oldfashioned book reading or connect to the Internet to find interesting material to read. Membership in book clubs where members regularly meet to discuss assigned readings can also make the reading experience more enjoyable for students. ACKNOWLEDGEMENTS The researcher wishes to thank her family, especially her five-year old daughter Ingrid, for the inspiration to continuously upgrade her understanding of the world that she may have more insights to share, especially with young minds. 17 | P a g e REFERENCES Abidin, M., Pour-Mohammadi, M., and Jesmin, A. (2011). A survey of online reading habits of rural secondary school students in Malaysia. 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