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Showing posts with label 81 Johnson. Show all posts

 Journal of Linguistics and Language Teaching

Volume 13 (2022) Issue 2


Disciplinary Differences for Undergraduate ESL Writers in University Courses in the United States


K. James Hartshorn (Provo, USA), Norman W. Evans (Provo, USA), Jesse Egbert (Flagstaff, USA) & Amy Johnson (Provo, USA)


Abstract

Building on previous research, this study explores differences in university professors’ perceptions about writing from the beginning to the end of the baccalaureate experience across five common disciplines including biology, business, computer science, engineering, and psychology. Survey data provide insights regarding the relative importance of various aspects of writing along with information about the volume of writing, the extent to which feedback was provided and resubmissions were allowed, the types of writing completed for exams, the greatest writing challenges, and the most salient writing purposes across disciplines and over time. While factors such as the writing challenges students faced, seemed unaffected by discipline or time in a particular discipline, other factors were noticeably influenced by the students’ specific discipline, whether students were at the beginning or end of their baccalaureate experience, or both. These factors included distinct differences in the purposes of writing as well as different perceptions of the importance of various aspects of writing across disciplines. An understanding of both these commonalities as well as the differences should be useful for practitioners and university administrators as well as the students themselves. 

Keywords: English as a second language, second language writing, learning to write, writing to learn, writing within the disciplines




1   Introduction

Writing is an integral part of a student’s academic experience. Nearly all post-secondary institutions in the United States require at least one writing course to ensure that students have a solid writing foundation early in their academic careers. Such courses may be based on different pedagogical perspectives emphasizing particular forms of writing, such as the writing process itself, the notion of the writer as a member of a social community or the distribution of social and economic power. Such approaches towards writing are all likely to benefit students and their writing in different ways. Yet, one reason many university students struggle is because of the difficulty of producing writing that is appropriate to the expectations of their chosen disciplines (McCarthy 2020, Tasker 2022). A previous study has examined how well undergraduate ESL students are prepared to engage in discipline-specific writing at the beginning of major study in fields such as biology, business, computer science, engineering, and psychology (Hartshorn & Evans 2019).

Nevertheless, little is known about how writing expectations may change as students move through their discipline-specific coursework towards graduation. Therefore, this study was designed to help researchers, practitioners, and educational administrators better understand the answers to these questions. It contrasts perceptions of discipline-specific writing at the beginning of baccalaureate coursework with writing of students nearing graduation based on responses from faculty within five common disciplines for ESL students. These responses provide important insights for those interested in the language development of international students studying at English-medium universities.  


2   Literature Review

2.1 General Aspects

Effective writing skills are essential for students to be successful in their academic pursuits and employment as well as in their personal lives (Graham 2019). Yet, learning to write effectively in post-secondary institutions is fraught with numerous challenges and divergent perspectives (Hyland 2019). Researchers have suggested that writing expectations can vary greatly from one class to another (McCarthy 2020, Tasker 2022). The need for students to learn how to write in ways that meet expectations of specific disciplines is exemplified in the emergence of books such as Write Like a Chemist (Robinson, Stoller, Costanza-Robinson & Jones 2008), The Writers Guide to Psychology (Kaufman 2010), and Writing Like an Engineer (Winsor 2013), for example. 

Moreover, writing across disciplines is noticeably different from what is taught in intensive English programs and in first-year composition classes in terms of purpose, scope and form (e.g. Hartshorn & Evans 2019, Hartshorn, Evans, Egbert & Johnson 2017, Horowitz 1986, Johns 1981, Leki & Carson1994, Leki & Carson 1997). 

Discrepancies between introductory writing courses and needed applications of writing skills raise important questions about the appropriateness of these courses to prepare students to successfully engage in the kind of discipline-specific writing required in their studies. They also raise questions about whether adjustments in pedagogy might improve student mastery of the writing skills they need. Therefore, the present study was initiated with the hope of helping writing practitioners to adequately prepare their students for upper-division writing within their disciplines and for discipline-specific writing tasks they will encounter following graduation. 

In order to contextualize this study, its findings, and implications, we now briefly examine the most relevant literature that addresses writing across disciplines including the relative importance of writing, the varied amounts of writing, the types and purposes of writing, the writing feedback students receive, and the greatest writing challenges students face in undergraduate study.

While few writing practitioners would dispute that “writing is one of the most difficult skills” (Barkaoui 2007: 35) second language learners need to master and that teaching writing can be extraordinarily challenging, writing may not be perceived as the most critical skill for students at the undergraduate level. In their analysis of the relative importance of reading, writing, listening, and speaking for baccalaureate students at the beginning of major study, Hartshorn, Evans, Egbert & Johnson (2017) found that while writing was generally viewed as important to professors, it was perceived to be less important compared to reading and listening, but more important than speaking. This view of the relative preeminence of receptive skills is consistent with findings from Johns (1981), based on the perceptions of university faculty, and findings from Christison & Krahnke (1986), based on the perceptions of university students.  

While it is reasonable that receptive skills such as reading and listening would be critical for learning at the outset of the undergraduate experience, Johns (1981) suggested that productive skills may become more important for students in their upper-division classes. If productive skills grow in importance as students approach graduation and prepare for graduate study or entering the workforce, these changes need to be better understood. Such insights could enhance writing instruction and facilitate writing development for matriculated university students.  

Another fundamental question relates to how much writing students produce and whether the number of pages students write varies across disciplines and over time during their baccalaureate study. Previous research has identified differences across disciplines in the number of pages students write. For example, Garbati et al. (2015) analyzed undergraduate university writing in business, history, and kinesiology and found that history students were required to produce nearly twice as much writing as students in business or kinesiology. Likewise, Graves et al. (2010) noted that students in the humanities had to produce over twice the number of pages compared to students studying in the social sciences. Furthermore, Moran (2015) observed that undergraduates studying arts, humanities, and social sciences were assigned significantly more writing than those studying Engineering, mathematics, or other science-based disciplines. Finally, Hartshorn & Evans (2019) reported that students in biology and psychology produced significantly more writing than students in Business or Computer Science. Such findings are useful and provide practical guidance to inform writing pedagogy designed to prepare students for writing within specific disciplines. However, these findings say nothing about how the number of pages of writing may vary as students move from the beginning to the end of their baccalaureate studies


2.2 Writing Perspectives 

A broader but equally important question has to do with the various writing purposes found in discipline-specific courses. For example, one perspective in practice has been described as Writing to Learn (WTL) (e.g. Klein, Haug & Bildfell 2019). It is based on the notion that “student thought can grow, develop, and be clarified through the writing process” (Bazerman, Little, Bethel, Chavkin, Fouquette & Garufis 2005: 57). Young (2006) described this kind of writing as expressive, personal discourse that leads to self-discovery for the writer and other closely trusted individuals. This might include summarizing, synthesizing, or applying knowledge in personal journals, diaries, or notebooks. This might also include certain kinds of writing within the learning community that could be considered interactive, conversational or dialectic (Young 2006).   

Another approach is Writing in the Disciplines (e.g. Croft, Benjamin, Conn, Serafin & Wiseheart 2019). This is based on the “specialized language of the disciplines” and the “instructional concern for the specific form of writing students must gain competence in” (Bazerman et al. 2005: 66). This approach largely relates to student ability to write in ways that are consistent with the genres utilized in their respective disciplines. Young (2006) described this type of writing as transactional, public-oriented discourse that is designed to be informative or persuasive. This type of writing is closely associated with the notion of Learning to Write (LTW), where the stakes are higher and the process may take multiple drafts before an acceptable text is completed (Cox et. al 2014). While there may be overlap across them, these perspectives also suggest different emphases in the underlying purposes of writing tasks which students may encounter in their university study. If the purposes of writing in particular disciplines are more aligned with one or the other approach, identifying such insights could be very useful for writing practitioners 


2.3 Writing Feedback

Most educators would likely agree that if genuine learning is to occur, there must also be some form of assessment and feedback for students. Writing is no exception. Nevertheless, the literature suggests differences in the nature and amount of feedback that students receive from their professors. For example, Garbati et al. (2015) noted that only about 5% of the courses they analyzed included some type of writing feedback. In his study, Melzer (2009) documented that approximately 13% of the professors had students submit at least one preliminary draft of their writing for which the professor provided feedback that could be implemented before the final draft was due. Similarly, Graves et al. (2010) observed that in 14% of the writing tasks they examined, feedback was provided in the form of written comments or face-to-face interviews with the teachers or their assistants. In the study conducted by Hartshorn & Evans (2019), nearly 63% of student writing received some type of feedback for improvement. However, only 20% of the student writing was designed to be resubmitted after feedback was provided and revisions were made. For most writing, professors excepted students to refine the quality of their writing without feedback from them. Such findings raise doubts about whether the ongoing writing development for these ESL students is adequate as they approach graduation.


2.4 Writing Challenges

The literature also identifies some of the greatest writing challenges that university students face. For example, Soter & Smith (2016) indicated that despite multiple writing courses in their academic careers, students often struggled in areas such as spelling, grammar, clarity, coherence, and transitions,  just to name a few. Other studies produced similar findings across a variety of disciplines (e.g. Garbati et al., 2015, Moran 2013). Hartshorn & Evans (2019) found that the greatest writing challenges at the outset of discipline-specific study were associated with writing appropriately within the genre, clarity, grammar, organization, conciseness, and various issues associated with second language learning. However, the literature does not clarify whether such challenges remain constant throughout baccalaureate study or whether some challenges are resolved over time. 


2.5 Importance of Writing Features Across Disciplines

The literature also provides insights regarding the relative importance of specific features of writing across different disciplines. For example, Hartshorn & Evans (2019) examined the relative importance of specific features of writing across five common disciplines in the first semester of major study. The order of importance ranged from the appropriate use of discipline-specific vocabulary (viewed as important) to word choice, linguistic accuracy, academic vocabulary, and genre (viewed as somewhat important). The findings showed that word choice was more important in business than in computer science or engineering. Academic vocabulary in writing was more important in biology than in computer science,  and more important in business than in computer science. Linguistic accuracy in writing was more important in psychology and business than in computer science. While these insights should be very helpful to practitioners who prepare ESL learners to write within specific disciplines, the literature does not clarify whether these priorities remain consistent over the course of baccalaureate study or whether particular features may become more important than others in upper-division coursework.  

Similarly, the literature has identified the most common writing purposes for these same five disciplines. For example, Hartshorn & Evans (2019) found that the most frequent writing purposes across the five disciplines during the first semester of discipline-specific study included emphases such as demonstrating, synthesizing, and applying knowledge along with reinforcing learning. These purposes seem largely associated with the acquisition and demonstration of discipline-specific content knowledge learned in coursework. Other purposes, though, seem to relate more to developing various aspects of writing itself, including argument development, the application of genre, the clarification of thoughts, critical thinking, and effective communication. 

Unfortunately, the literature says very little about whether these purposes tend to change as students transition from entry-level to upper-division study.  


3  Methodology

3.1 Research Questions

This brief literature review has addressed a number of findings associated with student writing in U.S. universities and raised a number of questions whose answers could better inform writing pedagogy. Accordingly, the following research questions are articulated.    

  • How important is writing compared to reading, listening, and speaking during discipline-specific study and across disciplines? 

  • Are there differences in the following areas across disciplines and from the beginning to the end of baccalaureate study with regards to:

    • the volume of writing counted in pages, 

    • the percentage of writing that receives feedback, 

    • the percentage of writing that may be resubmitted after revision, 

    • the greatest writing challenges

    • the relative importance of writing features such as genre, linguistic accuracy, academic vocabulary, word choice, and discipline-specific vocabulary, and 

    • the most salient writing purposes


3.2 Data Elicitation

In order to answer our research questions, we created a survey similar to the one used by Hartshorn & Evans (2019) (Appendix). Data collection proceeded in several phases. First, we targeted the same U.S. colleges and universities that hosted the greatest numbers of international students (Farrugia & Bhandari 2013) used in our previous study. We identified culminating courses within each discipline at each of these institutions usually taken toward the end of the student’s undergraduate study. Decisions regarding these culminating courses were based on online degree requirements, programs of study, and course descriptions, as well as phone conversations with university faculty or staff. 

Though identifying the most appropriate beginning course for each discipline was relatively straightforward, it was more difficult to clearly identify the final courses within each discipline. Part of the challenge arose from our intentional avoidance of capstone courses because they varied widely in their purposes and credit hours, making them less comparable with each other. Another challenge arose from the fact that many majors offered a variety of elective courses towards the end of baccalaureate study that were designed to help students develop specializations within the discipline. Thus, unlike the introductory courses for each major, not all culminating courses were taken by all students. Despite these challenges, however, we utilized published resources and faculty consultation to determine the most appropriate courses to include in our study. 

We then identified faculty who taught these courses at each institution of interest and attempted to contact them by telephone to extend a personal invitation to participate in our online survey. As responses were limited, we next contacted professors by either leaving phone messages or emails inviting them to participate. We continued this process until we received an adequate number of surveys needed to address our research questions. Once these data were collected, we analyzed them and, where appropriate, we compared them with data from the first study. The survey was designed to allow us to report descriptive statistics along with several analyses of variance. 


3.3 Participants

Data were analyzed from 141 different professors from 80 different departments for the five majors examined (biology, business, computer science, engineering, and psychology). In some instances, multiple individuals responded from the same institution resulting in overlaps of varying sizes for each discipline at each institution. Where more than one quantitative response was provided from the same institution, values were averaged. Respondent information is summarized in Table 1:

Table 1: Participating Professors and Departments by Discipline 

Participating professors within each major were asked to indicate the average percentage of ESL learners within the specific class being used for analysis in this study. The results are presented in Table 2: 

Majors

    M

  SD

Business

29.47%

20.208

Computer Sci

28.67%

21.453

Psychology

15.33%

13.624

Engineering

14.90%

13.351

Biology

13.68%

  9.340

Table 2: ESL Percentages Reported by Discipline

These results suggest differences across disciplines, F(4,136)=6.617, p<.001) where more than a quarter of the students in business and computer science were reported to be ESL learners, nearly twice the percentage reported for the other disciplines. Business had a higher reported percentage of ESL learners than psychology (p=.011, d=.821), engineering (p=.004, d=.851), or biology (p=.003, d=1.00). Similarly, computer science also had a higher reported percentage than psychology (p=.057, d=.742), engineering (p=.033, d=.771), or biology (p=.021, d= .906). The results of this study should be seen in light of these findings.


4   Results and Discussion

The results associated with each research question are presented below, starting with the relative importance of writing compared to the other language skills at the beginning and the end of baccalaureate study. Since there are many different research question components, a brief discussion will accompany each set of results in an effort to help contextualize these findings.  


4.1 Relative Importance of Writing

Respondents indicated the level of importance for each of the four language skills. The four-point scale included (1) not important, (2) somewhat important, (3) important, and (4) very important. Results did not differ from previous study showing that listening and reading were perceived to be most important, followed by writing, and then speaking (Hartshorn, Evans, Egbert & Johnson 2017). Nevertheless, writing was the only skill that demonstrated a meaningful increase in importance from the beginning (M=2.73, SD=.864) to the end of baccalaureate study (M=3.08, SD=.953), F(1,252)=9.57, p=.002, notwithstanding a relatively small effect size, d=.385. This finding provides some evidence that the productive skill of writing may be more important in upper-division courses as suggested by scholars such as Christison & Krahnke (1986) and Johns (1981). Moreover, this combined data from the first semester of discipline-specific study to the end of baccalaureate study showed differences for the importance of writing across majors as illustrated in Figure 1. This indicates that writing was perceived to be most important in psychology and business and less important in computer science and engineering: 

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Figure 1: The Relative Importance of Writing across Disciplines


4.2 Volume of Writing

The second research question included six components beginning with the number of pages of writing required across disciplines and from the beginning to the end of baccalaureate coursework. Though no significant difference was observed for the number of pages written by students from the beginning to the end of their discipline-specific study, there was a significant difference across the disciplines themselves, F(4,167)=3.733, p=.006. This is illustrated in Figure 2, which shows that students in engineering courses produced significantly more pages of writing than those in computer science:

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-12-10 at 9.48.58 AM.png

Figure 2: Number of Pages of Writing across Disciplines

These findings suggest that on average, engineering students might expect to write over 22 more pages per course than those studying computer science, and that biology students could expect to write over 15 more pages than the latter. It is important to note, however, that differences between the amounts of writing in engineering and computer science may be due to distinctions in how writing is conceptualized in these disciplines. While writing within biology, psychology, and business is likely to fit within commonly understood notions of writing, writing in engineering often includes mathematical solutions or proofs (sometimes written by hand) used to solve specific engineering problems. Similarly, computer science may include samples of code designed to perform certain functions. Therefore, while much of the writing in these disciplines may look similar to other disciplines, some of it includes elements not found in other disciplines and may therefore not have the same rhetorical functions.        


4.3 Feedback on Writing

The next question addressed the percentage of writing that receives feedback. The overall mean percentage of writing that receives some form of feedback was 61.36% (SD=36.88). No significant difference was observed across time or discipline. However, there was a difference in the percentage of feedback across the disciplines in the first semester of major study, F(4,109)=3.320, p=.013. This is largely explained by one significant difference in feedback between psychology and computer science in the first semester of major study (p=.006, d=1.139), as plotted in Figure 3. This may reflect psychology professors’ efforts to help their students to become better writers, especially at the beginning of major study. This is in contrast to computer science where there seems to be much less feedback within the discipline at the beginning of study. Though we see extensive spread in the percentage of feedback provided in the first semester of major study, later, these percentages are clustered much more tightly, resulting in no significant differences close to graduation:

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-12-10 at 12.02.17 PM.png

Figure 3: The Percentage of Writing Receiving Feedback across Disciplines and Time 


4.4 Resubmissions of Writing

Closely related to feedback is the percentage of writing that may be resubmitted after revision. Differences were noted across the disciplines during the first semester of major study, F(4,61)=3.920, p=.007. For example, biology allowed for significantly more resubmissions compared to computer science (p=.047, d=1.305) and engineering (p=.021, d=1.365). A statistically significant difference was also observed across disciplines over time, F(4,182)=2.772, p=.029. These differences are plotted in Figure 4:    

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-11-04 at 9.57.47 AM.png

Figure 4: Resubmissions Allowed by Disciplines over Time 

Though the small increases were negligible from first-semester to upper-division courses for computer science and engineering, declines were more dramatic for psychology, F(1,36)=5.242, p=.028, d=.739, business, F(1,38)=8.158, p=.007, d=.884, and biology, F(1,43)=9.941, p=.003, d=.974. These large effect sizes may suggest an expectation for professors in some disciplines such as biology, psychology, and business to encourage writing as a process that results in a better final product and that may foster greater writing development. 


4.5 Writing Challenges

The next research question addressed potential differences in the writing challenges observed across disciplines and in the first-semester courses of major study compared to the upper-division courses. The four-point scale used for this analysis included (1) not a challenge, (2) somewhat challenging, (3) challenging, and (4) very challenging. Just four categories were used since the scale was unidirectional and additional categories would have made it difficult to provide respondents with clear semantic distinctions across categories. No significant differences were observed across disciplines over time, though there were statistically significant differences across the types of challenges themselves, F(17,2207)=13.353, p<.001. In Table 3, seven homogeneous subsets are presented for the 18 writing challenges included in this study. Note that challenges differ statistically where there are no overlapping asterisks (*) across subsets: 





Homogeneous Subsets

Writing Challenges

N

M

SD

1

2

3

4

5

6

7

English is second language

125

2.67

0.957

*







Poor grammar

125

2.66

1.025

*







Lack of clarity

124

2.46

0.949

*

*






Vocabulary

127

2.35

0.920

*

*

*





Poor organization

122

2.31

0.971

*

*

*





Poor paraphrasing

123

2.22

1.060


*

*

*




Poor basic writing skills

125

2.22

0.980


*

*

*

*



Synthesizing

124

2.20

1.004


*

*

*

*



Not Concise

123

2.20

0.983


*

*

*

*



Poor mechanics

123

2.14

0.961


*

*

*

*

*


Writing process

124

2.09

0.954


*

*

*

*

*


Not understand content

123

2.06

0.926


*

*

*

*

*


Inadequate citations

123

1.97

1.040



*

*

*

*


Lack of critical thinking skills

123

1.86

0.917




*

*

*

*

Lack of time

122

1.80

0.915




*

*

*

*

Irrelevant content

123

1.80

0.877





*

*

*

Discipline-specific features

125

1.76

0.787






*

*

Lack of motivation 

121

1.49

0.818







*

Sig.

 

 


.16

.14

.05

.06

.14

.08

.21

Table 3: Writing Challenges across All Majors and Times

Though there is fairly extensive overlap across the homogenous subsets, it is noteworthy that on average, the greatest challenges register between somewhat challenging and challenging in terms of severity, rather than approaching very challenging. This may suggest that professors perceive these difficulties as problematic, but not as debilitating. While some writing struggles may be closely related to others, several of the greatest challenges seem more associated with language issues rather than content or rhetorical expectations. These include descriptions such as English as a Second Language, poor grammar, lack of clarity or vocabulary issues. Subsequent challenges seem to be more related to specific writing conventions and expectations, such as poor organization, poor paraphrasing, poor basic writing skills, trouble synthesizing, and not being concise. This may support the observation that for second language learners, linguistic skills may lag behind rhetorical aspects of writing (Hartshorn, Evans, Merrill, Sudweeks, Strong-Krause & Anderson 2010, Hartshorn & Evans 2015), and that ESL students may benefit from additional opportunities to continue to develop language skills (e.g. grammatical, lexical, mechanical accuracy) throughout their baccalaureate study.  


4.6 Aspects of Writing 

The next research question examined five aspects of how writing might be evaluated including genre (i.e. discipline-specific patterns and structures of writing within the field), word choice (i.e. writers using vocabulary accuracy to convey meaning with precision), academic-level vocabulary (i.e. words being academic and less colloquial or conversational), discipline-specific vocabulary (i.e. students using the specific vocabulary of the discipline), and linguistic accuracy (i.e. grammar and mechanics such as spelling, punctuation, capitalization). Means and standard deviations are presented in Table 4: 



First Semester

Near 

Graduation


Total

Aspect

Major

  M

SD

  M

SD

  M

SD

Genre

Biology

2.27

1.02

2.38

1.10

2.32

1.05


Business

2.29

1.14

2.36

0.93

2.33

1.01


Computer Sci

1.98

1.24

2.41

0.91

2.20

1.09


Engineering

1.79

0.95

2.39

0.99

2.13

1.01


Psychology

2.18

1.10

3.05

1.17

2.63

1.21


Total

2.10

1.09

2.50

1.03

2.32

1.07









Word

Biology

2.77

0.90

2.79

0.83

2.78

0.86

Choice

Business

3.24

0.84

2.67

0.85

2.90

0.89


Computer Sci

2.08

1.20

2.82

1.05

2.46

1.17


Engineering

2.27

0.88

2.68

0.94

2.50

0.93


Psychology

2.73

0.98

3.23

0.87

2.99

0.95


Total

2.63

1.03

2.81

0.92

2.73

0.97









Academic

Biology

2.82

1.04

3.13

0.74

2.97

0.91

Vocabulary

Business

2.66

0.85

2.24

0.97

2.41

0.94


Computer Sci

1.58

0.75

2.50

0.96

2.06

0.98


Engineering

2.38

1.02

2.64

1.03

2.53

1.02


Psychology

2.40

0.75

2.77

0.87

2.60

0.83


Total

2.39

0.98

2.63

0.96

2.52

0.97









Discipline

Biology

3.06

0.83

3.17

0.96

3.11

0.89

Vocabulary

Business

3.35

0.76

2.73

0.88

2.98

0.88


Computer Sci

2.78

1.30

3.00

0.82

2.89

1.07


Engineering

2.90

1.01

2.86

0.93

2.88

0.96


Psychology

2.83

0.89

3.14

0.89

2.99

0.89


Total

2.99

0.97

2.95

0.90

2.97

0.93









Linguistic

Biology

2.43

0.74

2.63

0.77

2.53

0.75

Accuracy

Business

2.83

0.98

2.42

0.97

2.59

0.98


Computer Sci

1.88

0.94

2.27

1.03

2.08

1.00


Engineering

2.24

0.93

2.50

1.04

2.39

0.99


Psychology

2.88

0.92

3.09

0.92

2.99

0.91


Total

2.45

0.96

2.57

0.98

2.51

0.97

  Scale: 1 = not important, 2 = somewhat important, 3 = important, 4 = very important

Table 4: Aspects of Writing by Majors and Time

Our analysis revealed statistically significant differences across the importance of writing features, F(4,1188)=15.01, p<.001. These individual differences are illustrated in Figure 6, which shows that discipline-specific vocabulary was seen as more important than the other features and that word choice was more important than genre. Though there were no significant differences across time or discipline for discipline-specific vocabulary or genre, differences were observed for word choice, academic vocabulary, and linguistic accuracy:

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-12-11 at 9.37.31 AM.png

Figure 6: The Relative Importance of Writing Features


4.7 Word Choice

The aspect of word choice refers to the writer’s accurate and precise use of vocabulary. There was a statistically significant interaction between time and discipline for word choice F(4,227)=3.703, p=.006. Though the change over time was not significant for biology, engineering or psychology, there was a statistically significant increase in the importance of word choice for computer science (p=.029, d=.656), and a significant decrease for business (p=.017, d=.675), as illustrated in Figure 7:

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-11-06 at 3.42.09 PM.png

Figure 7: The Importance of Word Choice across Majors and Time

Nevertheless, the importance of word choice regresses towards the mean, as students get closer to graduation both in computer science (with the lowest score in the first semester) and business (with the highest score in the first semester). This observation suggests that in computer science, professors are more concerned with the basic functionality of student writing in the first semester than they care about linguistic precision, but that they expect the writing to become more accurate as students approach graduation. Though it is not clear why word choice appears to be less important in business as students near graduation, it may become less relevant as students improve, especially if word choice is strongly emphasized in the first semester, as these data suggest. 


4.8 Academic vocabulary

The category academic vocabulary refers to students' choice of words that is more formal and specialised, as opposed to words considered as more conversational. Though there was a statistically significant interaction effect for discipline over time, the effect size was too small to be meaningful. However, the largest differences were observed across disciplines, F(4,227)=5.985, p<.001. Academic vocabulary was most important in biology, which differed significantly from business (p=.046, d=.608) and computer science (p<.001, d=.966). Figure 8 plots the importance of academic vocabulary across disciplines from first-semester to upper-division courses:  

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Figure 8: The Importance of Academic Vocabulary across Majors and Time

Though most changes over time within the disciplines were small, this difference in the use of academic vocabulary is largely influenced by the comparison between the first-semester and the upper-division discipline-specific courses in computer science (p=.003, d=1.068). This result for computer science seems similar to that of word choice above. 


4.9 Linguistic Accuracy 

Though no meaningful differences in terms of linguistic accuracy were observed across time, statistically significant differences were observed across the disciplines, as shown in Figure 9:      

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Figure 9: Differences across Majors for Linguistic Accuracy

Linguistic accuracy was more important in psychology than engineering or computer science and more important in business than computer science. These differences might be associated with the varied types and purposes of writing within these disciplines. For example, accuracy may be more valued in psychology and business where the writing of a report or a proposal may be considered the end product where the stakes are highest. However, in engineering and computer science, the most important end product may be something more tangible such as a prototype built by the student or software that may function well despite limitations in the writing associated with these artifacts. In such cases, the accuracy of the writing may not be perceived as critical as a tangible product.


4.10 Writing Purposes

Another research question addressed differences in the writing purposes across disciplines and from the beginning to the end of baccalaureate study. A four-point scale was used, including (1) not part of the course, somewhat important (2), important (3), and very important (4). Mean responses ranged from nearing somewhat important to beyond important. The most important of these purposes include demonstrating, synthesizing, applying knowledge, analysis, and critical thinking. Nevertheless, some purposes were more important than others, as statistically significant differences were observed across purposes, F(16,2298)=25.057, p<.001. This is illustrated in Table 5, which shows five homogeneous subsets for the seventeen purposes included in this study (statistically significant differences occur where asterisks do not overlap): 





Homogeneous Subsets

Writing Purpose

N

M

SD

1

2

3

4

5

Demonstrate knowledge

137

3.11

.872

*





Synthesize knowledge

136

3.10

.976

*





Analysis

137

3.07

.979

*





Apply knowledge

137

3.07

.929

*





Critical thinking

136

2.96

1.043

*





Communicate effectively

137

2.90

.987

*





Discipline-specific develop

137

2.85

.999

*





Solve problems #

137

2.73

1.108

*

*




Reinforce learning #

136

2.70

.953

*

*

*



Clarify thoughts #

136

2.69

.962

*

*

*



Argument development #

136

2.35

1.098


*

*

*


Report writing 

137

2.28

1.194


*

*

*


Communicate w/ professor

136

2.24

.962




*


Develop writing skills #

135

2.17

1.130




*

*

Research writing #

135

2.07

1.201




*

*

Collaborative writing

134

1.93

1.091




*

*

Evaluate others’ work

136

1.78

.897





*

Sig.



 

.13

.08

.08

.15

.07

# Statistically significant differences across majors

Table 5: Writing Purposes across All Majors and Time 

Though there were no meaningful differences across disciplines for most writing purposes, there were several statistically significant differences across some of the disciplines. These are presented below, beginning with the most important purposes. 


4.11 Problem Solving

The first of these writing purposes is problem solving, which showed statistically significant differences across disciplines, F(4,132)=4.482, p=.002 (Figure 10):   

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Figure 10: The Importance of Problem Solving as a Writing Purpose for Each Discipline

Problem solving was most important in computer science and engineering, considered between important and very important. This is in contrast with business and psychology where problem solving was considered between somewhat important and important. These differences might be due to the practical applications of writing in computer science and engineering, as they suggest attempts to solve specific problems in computing or the application of technologies.


4.12 Reinforcing Learning

The next writing purpose that exhibited different levels of importance across disciplines was reinforcing learning, F(4,131)=3.393, p=.011. It is illustrated in Figure 11, which presents the opposite order of disciplines compared to the previous figure: 

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Figure 11: The Importance of Reinforcing Learning as a Writing Purpose for Each Discipline

Reinforcing learning was most important in psychology, where it was considered important, but differed significantly from engineering,  where it was merely considered somewhat important. This difference produced a large effect size. This could suggest possible differences in the purposes of these courses and the importance of reinforcing learning within these respective disciplines. While one primary reason for psychology classes may be to foster specific content learning, engineering classes may be more focused on particular applications of content knowledge. 


4.13 Clarifying Thoughts

Another writing purpose that varied in importance across the disciplines was clarifying thoughts, F(4,131)=2.779, p=.030 (Figure 12): 

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Figure 12: The Importance of Clarifying Thoughts as a Writing Purpose for Each Discipline

This writing purpose was judged as most relevant in psychology, where it was considered important, but differed statistically from engineering, where it was only considered somewhat important. This difference also generated a large effect size (d=.88). One observation that may be worth noting here is the apparent separation of disciplines, where fields more closely aligned with social sciences (i.e., psychology and business) seemed to differ from the other disciplines. While the accurate articulation of students' thoughts may be an important aspect of writing in many contexts, it may be less relevant where scientific facts and physical laws preempt differing theories, philosophies, or beliefs about social phenomena.


4.14 Argument Development 

The next writing purpose that differed in its importance across disciplines was argument development, F(4,131)=4.622, p=.002. This is illustrated in Figure 13: 

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Figure 13: The Importance of Argument Development as a Writing Purpose for Each Discipline

The figures show a substantial difference between psychology, where argument development was most important,  compared to computer science and engineering,  where it was just marginally important. Similarly, argument development was also more important in business than in engineering. As suggested in earlier analyses in the present study, these differences may be associated with variations in writing purposes within these courses and possibly within the disciplines themselves. It is conceivable that the purposes behind argumentation in writing are more relevant in disciplines such as psychology and business than in fields like computer science and engineering. 


4.15 Developing Writing Skills

The second to last writing purpose we will examine with differences across disciplines is developing writing skills, F(4,130)=4.786, p=.001 (Figure 14):       

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Figure 14: The Importance of Developing Writing Skills within Each Discipline 

The figures show that the development of writing skills is important in psychology, but that its importance in computer science and engineering is marginal at best. These comparisons, including their large effect sizes, may help explain some of the previous differences noted above and seem consistent with the finding shown in Figure 1 that writing was perceived as most important in psychology and business and less important in computer science and engineering. Whereas writing may be largely utilitarian in computer science and engineering, one important purpose for writing in psychology courses seems to be associated with developing the skills needed to write more effectively in the future.


4.16 Research Writing

The final writing purpose we examine in this study where there are differences across disciplines is research writing, F(4,130)=5.228, p=.001. These differences are displayed in Figure 15: 

Macintosh HD:Users:jameshartshorn:Desktop:Screen Shot 2015-11-04 at 10.31.14 AM.png

Figure 15: The Importance of Writing Research as a Writing Purpose for Each Discipline

Though writing research is most important in psychology, it is considered of marginal importance for business, computer science, and engineering. This finding underscores another possible difference in the purposes of these undergraduate courses. In some courses, research writing is an essential component that may be more summative in nature, but in other courses, it seems much less important compared to more practical communication that may function simply as a means rather than an end within the course. 


4.17 Implications of the Findings

Some areas of analysis showed similarities across the different disciplines and over the course of study within the disciplines. For example, language related challenges, such as grammar and vocabulary, seemed equally relevant across all disciplines. In their survey responses presented above, professors indicated that discipline-specific vocabulary and word choice were important regardless of the respective disciplines. They also indicated that writing purposes were similar across disciplines including demonstrating, synthesizing, analyzing, and applying knowledge. Despite these similarities, important differences were also observed. The following description is organized by discipline. 


4.17.1 Biology

Writing is viewed to be rather important in biology, and students can expect to produce fairly large amounts of writing throughout their studies. Being able to resubmit writing after revision is common at the beginning of study but not near graduation. This finding suggests that it would be important for students to master the writing expectations and conventions early in their academic career and then continue to be able to meet those expectations in subsequent semesters. Professors also have a particularly high expectation that students will effectively use academic vocabulary throughout their writing. 


4.17.2 Business

Like Biology, writing was viewed as quite important in business. Business also allowed for a relatively high number of resubmissions at the beginning of study, but not towards the end of study. This observation suggests the importance of developing writing skills at the beginning of study. This is particularly true of the strong focus on students’ ability to effectively develop arguments in their business writing. Professors have a high expectation for students to quickly learn to choose their words effectively at the beginning of their study within the discipline, though this expectation seems less of a concern in their upper-division classes.  


4.17.3 Computer Science

Writing in computer science seems largely utilitarian and focuses strongly on problem solving. Compared to the other disciplines, there is very little focus on developing writing as a skill and little interest in the development of argumentation, writing accuracy, or the use of academic vocabulary. Feedback on writing is quite limited and resubmissions are rarely allowed.  


4.17.4 Engineering

Like computer science, the primary purpose of writing in engineering is for problem solving. Though students in engineering produce the most writing, it is fraught with mathematical proofs and represents a different kind of writing than the ones found in biology, business, and psychology. Like computer science, writing in engineering at the baccalaureate level does not appear to be focused on the development of writing as a skill. There is little importance tied to argument development, accuracy, or clarifying thoughts, and very little writing is allowed for resubmission.  


4.17.5 Psychology

Like biology and business, writing was viewed as quite important in psychology. Students can expect to produce fairly high volumes of writing designed to help them reinforce their learning as well as to develop their writing skills. Emphases include developing argumentation, clarifying thoughts, and effective word choice. Feedback and resubmission rates are high at the beginning of major study but taper dramatically towards graduation. Also, writing accuracy and the development of research skills were the most important in psychology. 


5   Conclusion

These disciplinary profiles for writing during baccalaureate study highlight interesting similarities as well as differences. Regardless of the discipline, most students tend to struggle with the same kinds of grammatical and mechanical challenges in their writing. Yet, the purposes and functions of writing vary across disciplines. Though not mutually exclusive, it seems that many aspects of writing in engineering and computer science may be aligned with a writing-to-learn perspective. In these disciplines, writing seems to be a means to an end where the focus is on problem solving and content mastery. 

While facets of a writing-to-learn perspective are evident at the baccalaureate level in the other disciplines of biology, business, and psychology, we also see aspects of learning to write and writing in the disciplines that are not as apparent in engineering and computer science. In biology, business, and psychology, writing seems to be more than just a means to strengthen and assess learning – it is an end in itself, as demonstrated by its importance in these disciplines. There seems to be an explicit effort to develop student writing, as suggested by liberal resubmissions and the focus on developing argumentation, clarifying thoughts and the importance of linguistic accuracy within student writing.

This research explored writing differences across disciplines from the beginning to the end of baccalaureate study. Though writing challenges seem unaffected by the respective majors or by the question of whether students were at the beginning or end of their baccalaureate experience, other factors were influenced by the students’ disciplines, the point in the students’ baccalaureate experience, or both. These include differences in the purposes of writing and different perceptions of various aspects of writing across disciplines. Insights from this study should be useful for practitioners, university administrators, and the students themselves. Informed with these insights, stakeholders will be empowered to focus on where attention is needed the most on the journey towards developing skilled writers across disciplines.  




Appendices

Appendix A

Writing Survey

Please slide the level for each of the following statements:

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Authors:


K. James Hartshorn, Ph.D.

Assistant Professor

Brigham Young University

Linguistics Department

4061 JFSB Provo, Utah 84602, USA

Email: james_hartshorn@byu.edu


Norman W. Evans, Ph.D.

Professor

Brigham Young University

Linguistics Department

4048 JFSB Provo, Utah 84602, USA

Email: norman_evans@byu.edu


Jesse Egbert, Ph.D.

Associate Professor

Northern Arizona University

Applied Linguistics Department

BAA 315 Flagstaff, AZ 86011, USA

Email: Jesse.Egbert@nau.edu


Amy Johnson, M.A.

Brigham Young University

Linguistics Department

4064 JFSB Provo, Utah 84602, USA

Email: amsjohnso@gmail.com