Cracking the Case

Abstract

Research has noted an increase in the use of assessed group projects across disciplines in institutions of higher learning. Consequently, this study investigates the prompt for an assessed group case-study project in a sophomore business module in order to provide lecturers with tools and techniques for probing a prompt document. The authors use a task-analysis framework developed for task-based language teaching to examine the project’s requirements and chain of integrated tasks. The study shows that the project prompt was dense and complicated and the component tasks were highly interactive and complex. Further, the study reveals that group case-study projects can play an important role in developing the team skills needed for future real-life projects.

Keywords

case study business group work task complexity

The assessment of group projects is a recent widespread phenomenon in the United Kingdom. A university-wide needs analysis at a U.K. university (Thondhlana & Gao, 2009) reveals the increasing use of assessed group projects across the university’s diverse programs, a development that other studies have also noted (e.g., Ashraf, 2004; Chapman, Meuter, Toy, & Wright, 2006; Evans & Morrison, 2011; Hansen, 2006; Victoria University of Wellington, 2004). Consequently, our study investigates the expectations of an assessed group case-study project by analyzing the assignment document in the business school’s first undergraduate module, Computers in Business. We explore the tasks identified in the project prompt document using a task-based framework and investigate the linguistic input of this document and the requirements for the final oral and written products.

Task has been used as a unit of analysis for teaching and learning both linguistic and subject content since the early 1990s. Definitions of task emphasize goal-directed activities involving collaborative interaction. Many have suggested that classroom language tasks should simulate real-world communication (Bygate, Skehan, & Swain, 2001; Crookes, 1986; Ellis, 2003; Mohan & Smith, 1992; Skehan, 1998; Van den Branden, 2006). Skehan (1998), for example, stated that in task-based learning, “meaning is primary; there is some communication problem to solve; there is some sort of relationship to comparable real-world activities; task completion has some priority; (and) the assessment of the task is in terms of outcomes” (p. 95). Long and Crookes (1991) distinguished between target or real-world tasks and pedagogical tasks, explaining that target tasks are those that students will eventually do with language (e.g., in academic study, at assessment centers, at work) and that pedagogical tasks are the activities in the language classroom. Pedagogical tasks are usually designed to approximate the target tasks in terms of linguistic aspects, content, stages, available options, and so on (Long, 1989). Colbeck, Campbell, and Bjorklund (2000) found that “students liked working on ‘real-world projects’. . . problems faced by industry that had many possible solutions, and where the focus was more on the problem solving process than on calculating a predetermined right answer” (p. 70).

Although there are many studies of language-learning tasks that relate to task-based learning and teaching, group project tasks have received limited attention in the higher education literature (Colbeck, Campbell, & Bjorklund, 2000; Davies, 2009). Case studies, however, are a popular learning mode, especially in business schools (Hansen, 2006; Jackson, 2004) and in education. Case studies provide a window into the real world and promote the collaborative exploration of a genuine situation with all the twists and turns that occur in real life. By promoting collaborative discussion and the sharing of experience, ideas, and varying perspectives, “this problem-based methodology is designed to encourage students to develop the interpersonal, analytical and decision-making skills as they link theory with practice” (Jackson, 2004, p. 214). This interpersonal exchange helps students learn to respect the opinions of others and to compromise or restructure their own point of view when necessary (Smith, 2009), so it has much in common with task-based learning.

Complex case-study projects often consist of a chain of pedagogical tasks that lead to final, assessed product. The process of selecting, organizing, grading, and sequencing complex tasks into task chains—a linked series of facilitating tasks that relate to or build on each other—in order to create a target task is often identified as challenging (Ellis, 2003; Willis & Willis, 2007). To crack the case, the group must interact collaboratively to explore and negotiate the series of tasks.

This study investigates the project prompt for an assessed group case-study project in an undergraduate module, Computers in Business, within a school of business. We identified the chain of tasks in the project prompt, and then, using a task-analysis framework, we scrutinized and evaluated these tasks in terms of type and complexity. We also investigated the linguistic input of the prompt document and the two recommended readings using T-unit analysis, a vocabulary profiler, and concordance software tools. Finally, we explored the requirements for the final oral and written products.

Data and Methods

Our data for this study consisted of the six-page prompt for a group case-study project and two recommended supplementary readings. In addition, we conducted two interviews with the business module lecturer to clarify issues relating to the project and consulted the undergraduate student handbook. These interviews were a follow-up to our initial interview for the university-wide needs analysis (Thondhlana & Gao, 2009).

The group case-study project is part of the undergraduate, qualifying year business school module N11101 Computers in Business that is offered in the first semester of the academic year. This project requires students to prepare a design bid for an exhibition with online promotional support for Reduce IT, a government-sponsored plan to help small and medium-sized enterprises reduce their environmental impact through improved computing. The project has two outcomes: a 4,000- to 5,000-word report and a 10-minute presentation. Although the format of the case study remains much the same each year, the content can be substituted. The project, which carries the bulk of the module assessment (60%), is intended to develop and test a range of competencies, including the ability to use information-communication technology, prepare specifications, plan a budget, formulate strategy, work in a group, prepare a collaborative document, and make a presentation.

While students work on collaborative projects in other modules, we chose to study this particular project at the qualifying, or first-year, level because most of the students we teach in a U.K. foundation program plan to study business. Also the project represents the type of case study that students encounter at an assessment center in their second year as part of the internship-placement process as well as activity that they will engage in later in the workplace. It therefore prepares students for both placement and employment.

Initially, we read the project-prompt document closely to identify the constituent tasks. Next, we interviewed the module lecturer to develop a better understanding of the project’s task requirements. Then we analyzed the data to understand the nature of the requirements in terms of type and complexity of the component tasks. A further interview with the lecturer clarified a number of issues relating to the project.

Task Type

We determined task type by analyzing the nature of the task’s features (e.g., its format and instructions) and the interactivity that the task would generate. In terms of interactivity, we analyzed the project prompt for tasks that compel or stimulate students to negotiate and reach consensus. Research has shown that certain task features generate more interaction than do others (Duff, 1986; Ellis, 2006; Garcia-Mayo, 2007; Long, 1989; Pica & Doughty, 1985; Skehan, 1998), but certain interactive variables, such as those relating to information exchange, may overlap. Table 1 outlines the features and interactivity of the task types that we investigated.

Table 1.

Features and Interactivity of Task Types

Features	Interactivity	Task Type
Flexibility	Tight (more interactive)	Tasks with fixed subtasks that the group cannot change, so they must agree
Flexibility	Loose (less interactive)	Tasks with flexible subtasks that the group can change, so they do not need to agree
Answers and solutions	Closed (more interactive)	Tasks with subtasks having a limited number of answers or solutions that the lecturer has predetermined
Answers and solutions	Open (less interactive)	Tasks having many possible answers or solutions that the lecturer has not predetermined
Interpretation	Interpretive (more interactive)	Tasks requiring participants to make individual interpretations and then negotiate these with their peers
Interpretation	Procedural (less interactive)	Tasks requiring participants to deal with facts and reach decisions without making interpretations
Agreement	Convergent (more interactive)	Tasks requiring agreement
Agreement	Divergent (less interactive)	Tasks not requiring agreement
Information exchange	Required information exchange (more interactive)	Tasks in which participants must exchange information
Information exchange	Optional information exchange (less interactive)	Tasks in which participants may choose to share their own ideas or opinions in relation to the information
One- or two-way exchange	Two-way (more interactive)	Information exchange is reciprocal between two or more participants (real discussion)
One- or two-way exchange	One-way (less interactive)	Information exchange moves from one participant to the next in a series of minipresentations
Negotiation	Extensive negotiation (more interactive)	Tasks requiring extensive negotiation and agreement
Negotiation	Little or no negotiation (less interactive)	Tasks requiring little or no negotiation

Task Complexity

We determined task complexity by examining the inherent characteristics of the task that relate to the nature of the input, the task conditions, the operational processes, and the required outcome (Ellis, 2003; Robinson, 2001). Robinson saw these information-processing demands of the task as resulting from the characteristics that the task designer has manipulated. In addition, other studies (Brindley, 1987; Candlin, 1987; Foster & Skehan, 1996; Garcia-Mayo, 2007; Prabhu, 1987; Robinson, Ting, & Urwin, 1996; Skehan, 1998, 2003) provide us with insights into task complexity. Based on these studies, our own perceptions of the nature of the academic group tasks, and our consultations with the lecturer, we decided to analyze task complexity in terms of three criteria: cognitive complexity, code complexity, and communicative stress.

First, the cognitive complexity of the task stems from the conditions of the input—in our case, the project document (including the brief and guidelines)—and the cognitive demands of processing it. These cognitive demands are affected by participants’ familiarity with the genre, content, task, academic conventions, cultural expectations, and group processes. We analyzed the cognitive complexity of the task by considering eight conditions: density, format, degree of structure, complexity of instructions, clarity, information type, sequencing, and familiarity. Table 2 describes these conditions.

Table 2.

Input Conditions That Affect the Cognitive Complexity of a Task

Input Conditions	Description
Density	Quantity, density, and length of information
Format (e.g., reading, listening, visual)	Written documents with visuals = less complex than written documents without visuals
	Oral information = less complex than written documents
	Pictoral documents = less complex than verbal information
Degree of structure	Whether information is highly organized
Degree of structure	Free-form documents are more complex than are clearly structured ones
Complexity of instructions	Number of elements in the information and the specificity of the instructions
Clarity	Whether the information is clear and sufficient
Information type	Static information remains the same throughout task.
	Dynamic information is more complex than static information is because the information describes a series of changing activities.
	Abstract information is more complex than are dynamic and static information because the information is used to form an opinion or justify a position.
Sequencing	Multiple actions to be performed simultaneously
Familiarity	Whether discourse genre, content, task, academic conventions, cultural expectations, and group processes are familiar to participants (lack of familiarity causes complexity)

A task is cognitively complex if the input is a densely formatted (e.g., single-spaced), lengthy document consisting of a wide range of information, academic vocabulary, and complicated syntax. Documents of this nature require several readings in order to understand the specific details. Research on input format, or medium (Ellis, 2003; Prabhu, 1987), has noted that tasks with an oral input are easier to understand than those with a written input while those with pictorial input are easier to understand than those with verbal input. Diagrams and pictures make understanding easier. With regard to degree of structure, a free-form task is challenging if the input does not explicitly provide the steps needed to complete the task. Such tasks require several readings to identify all the necessary steps. The complexity of the instructions within a prompt document varies. A series of instruction elements makes a task more complex because the prompt must be carefully analyzed in order to fully understand it. Thus, the complexity of the instructions affects the clarity of the input—whether it is clear and sufficient—as do the density and structure of the prompt document. The information type affects the cognitive complexity of tasks in that dynamic information, which describes shifting activities, is more difficult to comprehend than static information but less difficult to comprehend than abstract information (Brown, Anderson, Shillcock, & Yule, 1984). Input about task sequencing requiring multiple actions to be performed at the same time is more complex than input about actions to be performed one at a time. Finally, participants’ familiarity or lack of familiarity with input affects their perception of the task complexity.

The second criterion of task complexity, code complexity, refers to the input’s linguistic features: the syntactic and lexical complexity of the project prompt and recommended readings. To analyze the code complexity, we examined both syntactic and lexical complexity. Syntactic complexity refers to the complexity of the sentence structure. Because a wide variety of both basic and sophisticated structures are available in any given text, we used a T-unit (minimal terminable unit) analysis, proposed by Hunt (1970), to analyze the syntactic complexity of the project document. Such an analysis provides an objective and reliable method of determining the overall complexity of language texts. A T-unit is the shortest unit “into which a piece of discourse can be cut without leaving any sentence fragments as residue” (p. 188). It consists of one “main clause plus any subordinate clause or non-clausal structure that is attached to or embedded in it” (p. 4). Research has identified a number of measures that indicate syntactic complexity, for example, (a) average length of a structure, or T-unit length (words per T-unit); (b) average length of a clause (words per clause); and (c) complexity ratio (number of clauses per T-unit as a measure of subordination). Studies exploring the relationship between syntactic complexity and text quality have found that Measures b and c are more helpful than Measure a while those that are not focusing on text quality have found Measure a to be equally helpful. In this study, we employed Measures a and c for a more balanced analysis.

For the T-unit analysis, we measured the average length of a structure (mean and standard deviation), within and across data sets, using the statistical software Statistical Package for the Social Sciences (SPSS). Then we conducted a t-test for comparison. A short T-unit length corresponds to 1 to 8 words per sentence, medium-length T-units correspond to 9 to 20 words per sentence, and long T-units correspond to 21 or more words per sentence (Bardovi-Harlig & Bofman, 1989; Beers & Nagy, 2007; Hunt, 1970; Kuiken & Vedder, 2009). We used the complexity ratio to measure clause subordination. A higher ratio of clauses indicates more embedded text structures and hence a high level of complexity. Again, we measured within and across data sets and made comparisons with a t-test. Although Excel, SPSS, or the Syntactic Complexity Analyzer could be used, we selected SPSS because of its flexibility.

Lexical complexity refers to complexity of the technical and subtechnical vocabulary used in the project prompt and related documents. Vocabulary profilers provide a lexical text analysis by identifying the word frequency in a text. VocabProfile (Cobb, n.d.) is based on Laufer and Nation's Lexical Frequency Profiler and identifies the words in a document in terms of “(1) the list of the most frequent 1000 word families, (2) the second 1000, (3) the Academic Word List [AWL],” and other words. Cobb noted that “a typical NS (Native speaker written text) result is 70-10-10-10, or 70% from first 1000, 10% from second thousand, 10% academic, and 10% less frequent words” and that the first and second 1,000 words appear quite frequently and provide about 80% coverage in most texts. But, Coxhead and Nation (2001) showed that generally 8.5% of the vocabulary in an academic document is from the AWL. This list includes 570 commonly occurring academic word families that are not included in the most frequent 2,000 words that can be highlighted using AWL Highlighter (n.d.).

We anticipated that due to the group focus within the project prompt, certain language items that include or collocate with the word group or team or that refer to the need to collaborate, negotiate, and reach agreement would be used frequently. Further, we anticipated the frequent use of language relating to the required or assessed components of the task, such as the exhibition or the presentation, and other language providing advice or outlining required elements of the project. We used the concordance selector of the Complete Lexical Tutor (Cobb, n.d.) to locate the frequency of lexical items for this purpose.

Finally, our third criterion of task complexity, communicative stress, is the level of stress learners are expected to experience when performing tasks of diverse degrees of complexity (Candlin, 1987). Skehan (1998) saw communicative stress as “the performance conditions for accomplishing a task” (p. 88). We identified a number of performance conditions as analytical variables in this study (Candlin, 1987; Foster & Skehan, 1996; Robinson, Ting, & Urwin, 1996). These conditions consist of the time limits available for the project, the number of steps or tasks involved, the sequence of operations, the sequence in which information is presented or clearly structured, and the extent to which participants are familiar with aspects of the project.

Eventually, this research needs to be further validated by following up the project prompt analysis with, for example, student interviews and an investigation of the support provided. Student interviews could provide information on task difficulty and would be especially useful if international students were compared with home students. But the study presented here is limited to an investigation of the project prompt, which includes elements that may assist teachers in evaluating the effectiveness of such assessment documents.

Results

The project prompt is a loosely organized document written by the lecturer to mimic briefs written for business consultants or an assessment center. The first part provides general information and project instructions in seven short sections. The second part—which has the large printed title “Your Project Brief—Reduce IT!”—outlines the expectations of the IT (information technology) project in four sections. The final, unmarked part provides information on the final assessment—the report and presentation—in four sections. Each section has a short, bold heading, but parts one and three are not obviously marked, so readers have to concentrate to identify the separate parts and task requirements. To facilitate our analysis of the project, we grouped the tasks according to their taxonomic relationship: reading the project prompt, reading the recommended readings, forming and organizing the group, planning the exhibition, preparing for the final assessment, and allocating marks. We then analyzed the tasks according to task type and task complexity.We present our findings in the following subsections. Figure 1 illustrates the chain of tasks in chronological order over the 8- to 10-week period. Readers would need to unpack the brief and guidelines to identify the various tasks and steps required to successfully complete this project.

Figure 1.

The chain of tasks in chronological order.

Reading the Project Prompt: Cracking the Case

We unpacked the project prompt in order to identify the underlying subtasks. Then we analyzed these subtasks according to task type and task complexity.

Task Type

The project prompt is a partially organized, free-form document consisting of several parts that outline the tasks involved. A close reading of the project prompt reveals a chain of linked tasks that the students need to identify in order to successfully complete the project.

The prompt is tight in terms of flexibility of the interactivity because the subtasks have to be fulfilled. The solutions are closed because the tasks must be completed (see Table 1). The task of reading the prompt is interpretive as students read the prompt individually before joining a group and negotiating with their group to collaboratively agree on a single interpretation of the steps and the requirements. For example, the prompt states that “students . . . are required to form their own groups and to select a team leader for the same.” Information exchange is required, and students must give their own ideas and opinions in a two-way interactive exchange (between 5 and 7 group members) involving extensive negotiation. The introduction of the prompt includes the following instructions:

This project involves completing a substantial piece of work as a cohesive and professional team. To ensure that this happens, your group will need to hold regular meetings to brainstorm ideas, plan and allocate work, make decisions, review progress, solve disputes, and otherwise manage the activity and performance of your team.

As a whole, the project requires the fulfillment of all tasks, so the subtasks are limited in terms of interpretation. Because of the organizational features and the multiple tasks involved, the students need to consult the prompt throughout the project in order to identify and clarify the specific requirements of each task.

Task Complexity

The results of our analysis of all three criteria of task complexity indicate that the prompt has a high level of complexity (see Table 3). To fully understand a text of this nature requires a higher order of reading and critical thinking (cognitive complexity) because the linguistic (code) complexity presupposes a high level of language proficiency that includes knowledge of technical, discipline-specific language; the AWL, Coxhead’s (2000) list of the words most needed to study at a tertiary level; and general, functional language, such as the language surrounding group assignments. Furthermore, students are expected to choose between relevant and irrelevant information. For example, the course description in the student handbook advises the following:

Table 3.

Task Complexity of Reading the Project Prompt

Cognitive complexity	contains dense, static, six-page, single-spaced written text and a visual features a complex, loosely organized structure requires familiarity with case-study approach, green computing, and the academic expectations of group work
Code complexity	contains complex sentences uses complex, dense academic language includes the functional language of group-assignment instructions
Communicative stress	identify assessment requirements and timelines identify steps in the project and develop sequence become familiar with case-study tasks, exhibitions, green-computing content prepare for group discussion of the document

You should also be aware that sometimes you might be given material in the case which is not relevant to the task which you have been set. Here, you will have to trust your judgement and ignore it; the inclusion of irrelevant material in your analysis may be penalised.

Thus, the task has a high potential for causing students to experience communicative stress.

We analyzed the project prompt for cognitive complexity using the criteria outlined in Table 2. The density of the document is high as it is a six-page, single-spaced document. The format includes substantial writing with only one visual, a diagram. The structure is loosely organized and contains many steps and tasks requiring simultaneous multiple actions that students have to identify, understand, and follow. The instructions are varied, including inflexible and flexible requirements, the need for creativity, advice, suggestions, and specific content. To effectively develop the project, students must have a good understanding of concepts such as exhibitions, green computing, and case-study tasks. Because of these elements, this project has a high level of complexity.

We also analyzed the project prompt for code complexity, using a T-unit analysis to measure syntactic complexity. We divided the prompt document into two sections—general instructions (Part 1) and project design (Part 2—) to determine whether complexity differed with mode. After identifying the T-units (i.e., main clause plus any subordinate clause), we measured syntactic complexity by counting the words in each section. Then we calculated the mean and standard deviation of the T-units in each section. Further, we conducted a t-test to determine whether there were any significant complexity differences between the two parts. Table 4 shows the mean T-unit length and the standard deviation for each section. The mean and standard deviation results revealed that both Part 1 and Part 2 of the prompt have long T-units with more than 20 words (20.63 and 24.38, respectively); therefore, both are highly complex. The t-test results showed that there is no statistically significant difference between the T-unit lengths of the two parts.

Table 4.

Mean T-Unit Length and Standard Deviation of Project Prompt

	Section	No. of T-Units	Mean No. of Words in T-Unit	Standard Deviation
Project prompt	Part 1	129	20.63	11.59
	Part 2	40	24.38	10.71
	Combined parts	169	22.52	11.19

Note: t-test results (.769) showed no statistically significant difference.

Similarly, as Table 5 shows, the results of the complexity-ratio analysis confirmed that while the complexity-ratio was higher for the project-design section than for the general instructions section, the complexity difference between the two parts was not statistically significant. The results show that while the design section is slightly higher in complexity, overall the document has a high level of syntactic complexity.

Table 5.

Syntactic Complexity of Project Prompt

	Section	Clauses	T-Units	Mean	Standard Deviation
Project prompt	Part 1	220	129	1.71	.861
	Part 2	75	40	1.92	.703
	Combined sections	295	169	1.76	.830

Note: t-test results (.586) showed no statistically significant difference.

A vocabulary profile analysis of the project prompt (see Table 6) showed that a significant proportion of words in the document (more than 75%) hailed from the first 1,000 word families and a very low proportion (less than 4%) from the second 1,000 word families. This result is somewhat different from that expected from a typical document (70% and 10%, respectively). Furthermore, the level of vocabulary from the AWL was higher than the 8.5% average found by Coxhead and Nation (2001), with Part 1 at 10.37% and Part 2 at 13.62%.

Table 6.

Lexical Complexity of Project Prompt

Measure	Part 1 (%)	Part 2 (%)
Words 1–1,000 (K1)	80.23	75.85
Function words (K1)	46.48	46.86
Content words (K1)	33.75	28.99
Words 1,001–2,000 (K2)	3.72	3.43
K1 + K2	83.95	79.28
AWL words	10.37	13.62
Off-list words	5.67	7.10

Note: AWL = Academic Word List.

Using concordance to investigate anticipated lexical items in the prompt, we found that group and team were, as predicted, used quite frequently to explain the group tasks in the project document. The word group was used (54 times, or 1.46%), mainly in Part 1, and the phrase group members was found 16 times (0.43%). Surprisingly, however, language relating to the students’ need to collaborate, negotiate, and reach agreement while doing the tasks was used much less frequently.

In addition, our analysis of the required project components revealed that various words indicating presentation (29 times, or 0.78%) and minutes (21 times, or 0.56%) were used much more frequently than other words. When investigating the AWL, we found that exhibit was used with exhibition 32 times (0.86%) in Part 2 (project design). We also found a variety of related collocations, including running an exhibition and support your exhibition, which could be unfamiliar to international students.

We found a prevalence of the use of modal verb constructions containing should, will, or must to provide advice or outline required elements of the project. Should was used 54 times (1.46%) to give instructions (see Table 7) and will was used 52 times (1.40%) whereas must was used only 20 times (0.54%) and ought to was used only once. We also found the use of should not (33 times, or 0.89%) to refer to what was unacceptable (“These should be Harvard Style, strict alphabetical (NOT by section) and not divided into books, journals, websites, etc.”). Choices marked by or (23 times, or 0.62%) also occur within the instructions, indicating that groups have to agree on a choice.

Table 7.

Concordance Lines With the Modal Should

should be avoided. The report		also be word processed
one or maybe two pages		be a maximum. However,
a maximum of ten minutes and	should	be attended by all
the text, however long lists		be avoided. The report
unequal final mark allocations		be considered exceptional

Overall, the document language is complex with some of the repetition and redundancy typical of actual business projects. The three modals should, will, and must highlight the required task elements and compose 3.4% of the document. Additionally, although the prompt includes a high proportion of words from the first 1,000 word families, it includes a higher proportion of AWL vocabulary, especially in Part 2 (project design), than the 8.5% average found by Coxhead and Nation (2001).

Finally, we found that students could expect to experience communicative stress from reading the project prompt. Because the case study report (CSR) meeting is held in the second week of the project, the students would have just a short time frame to identify the steps and assessment requirements of the assignment.

Reading the Recommended Readings

We explored the task type and complexity of the two recommended readings, which are real-world report documents located on the Internet for public readership. Then we compared our findings from this analysis with those from our analysis of the project prompt.

Task Type

We investigated the two recommended readings: Web documents on green computing and ways to reduce environmental impact through improved computing. The prompt recommended these two supplementary readings by stating that “the following are strongly advised as good initial reference sources.” The first reading, White Paper Eco-Technology Innovation: Advancing Global Sustainability Through Technology: Intel Leap Ahead (Intel, 2007) is an eight-page document recommending ecotechnological innovations to improve environmentally friendly computing. The second reading, Saving the Climate @ the Speed of Light: First Roadmap for Reduced CO2 Emissions in the EU and Beyond (Pamlin & Szomolányi, 2006), is a 44-page document linking ICT to sustainable development. Both documents provide models for the CSR required for the project assessment.

Task Complexity

Table 8 outlines the task complexity of the two readings according to the criteria. We found that both readings are highly complex because students need to develop familiarity with report documents and the concept of green computing. The first reading is an eight-page report in a two-column format with two graphs and a chart. It is clearly structured with a table of contents, executive summary, and bold subheadings. The second reading is a 44-page report in a two-column format with several full-page, colored pictures and various graphs and charts, which make it cognitively complex. It is also clearly structured with a table of contents, executive summary, and bold subheadings.

Table 8.

Task Complexity of Reading the Recommended Readings

Cognitive complexity	Read recommended academic sources and Web documents and select key ideas one dense, loosely structured, 8-page static document with graphs one dense, loosely structured, complex, 44-page static document with visuals
Code complexity	Interpret dense academic documents into spoken language Explain complex ideas in exchange of information on green computing Negotiate and agree on key topic components
Communicative stress	Read within a specific time frame Identify key ideas relevant for the project from the recommended readings Discuss and negotiate research identifying relevant key ideas Develop familiarity with green computing and exhibitions

We analyzed the two recommended texts (Reading 1 and Reading 2) to determine how the project document compared with related documents in terms of code complexity. First, we identified T-units from each reading and counted the number of words per T-unit (see Table 9). The mean and standard deviation results, which were confirmed by t-test results, showed no statistically significant difference between the two readings. This result is the same as what we found when we compared the project brief and general instructions.

Table 9.

Mean T-Unit Length and Standard Deviation of Recommended Readings

Reading	No. of T-Units	Mean No. of Words in T-Unit	Standard Deviation
Reading 1	133	19.83	10.87
Reading 2	122	18.25	9.41
Combined readings	255	19.07	10.21

Note: T-test results (.139) showed no statistically significant difference.

A complexity-ratio analysis confirmed, as Table 10 shows, that while the complexity ratio was higher for Reading 2 than for Reading 1, the difference between the two texts was not statistically significant. Both readings have a medium complexity ratio, indicating that they have a medium level of syntactic complexity.

Table 10.

Syntactic Complexity of Recommended Readings

Section	No. of Clauses	No. of T-Units	Mean Complexity Ratio	Standard Deviation
Reading 1	183	133	1.31	.514
Reading 2	177	122	1.44	.629
Combined sections	360	255	1.33	.519

Note: t-test results (.088) showed no statistically significant difference.

Next we compared the project prompt with the two recommended readings. We used the t-test analysis to determine the existence of any significant complexity differences. Table 11 shows the results of this comparison. The t-test analysis revealed statistically significant complexity differences between the prompt and the recommended readings in terms of both average T-unit length and complexity ratio. The results show that the project prompt is more complex than the two recommended readings.

Table 11.

Syntactic Complexity of the Project Prompt and the Recommended Readings

	Document	Number	mean	Standard Deviation	T-test Results
No. of T-units/mean no. of words per T-unit	Readings	255 T-units	19.07	10.21	Statistically significant difference (.045)
No. of T-units/mean no. of words per T-unit	Project prompt	169 T-units	21.26	11.19	Statistically significant difference (.045)
No. of clauses/mean complexity ratio	Readings	360 clauses	1.33	.519	Extremely significant difference (.000)
No. of clauses/mean complexity ratio	Project prompt	295 clauses	1.76	.830	Extremely significant difference (.000)

We performed vocabulary profile analysis to compare the project prompt and the two recommended readings. The results of this comparison are shown in Table 12. This comparison reveals that the number of words from the first 1,000 word families (K1) is close to the typical 70% in all three documents. The number of words from the second 1,000 word families (K2) is also similar for all three documents. But unlike the number of K1 words for each document, the number of K2 words for each is considerably less than the typical 10% (between 3.5% and 4.9%). In all three documents, however, the level of vocabulary from the AWL was above the 8.5% average provided by Coxhead and Nation (2001), with Reading 1 and Reading 2 (14.36% and 13.48%, respectively) being higher than the project prompt (12.13%).

Table 12.

Lexical Complexity of the Project Prompt, Reading 1, and the Executive Summary, Introduction, and Project Description in Reading 2

Measure	Project Prompt	Reading 1	Reading 2 (Executive Summary, Introduction, and Project Description)
Words 1–1,000 (K1)	77.79%	69.01%	73.60%
Function words (K1)	46.56%	34.29%	41.70%
Content words (K1)	31.24%	34.72%	31. 90%
Words 1,001–2,000 (K2)	3.55%	4.82%	3.66%
K1 + K2	81.35%	73.83%	77.26%
AWL words	12.13%	14.36%	13.48%
Off-list words:	6.52%	11.38%	9.26%
Total no. of words	3,832	3,218	4,696

The informational, syntactic, and lexical density and dynamic nature of the academic texts, as well as the systematic investigations required for exhibitions, make this reading task complex and stressful. Although these readings are longer than the project prompt, the lexical density of these documents is significantly less than that of the prompt because they include more visuals and more white space. But a lack of familiarity with the discourse genre, content, and cultural expectations of concepts (e.g., exhibition and green computing) can cause students to experience immense communicative pressure. In addition, students must then share and reach agreement on their interpretation of this information with the other group members so that they can include the information in their presentation and report. Thus, interpreting such dense written language into spoken language that is understandable to others is likely to be challenging and stressful for students.

Forming and Organizing the Group

We explored the process of forming and organizing the group in terms of its type and level of complexity.

Task Type

This series of tasks requires students to form groups of five to seven students and then to select a group leader and administrator. In addition, the group should allocate tasks and prepare a group status report (GSR) in time for the CSR meeting the following week. During group formation, a number of tasks must be performed. After selecting a group leader, who is responsible for coordinating the group-project activities, and an administrator, who is responsible for preparing the minutes that serve as a record of the group’s effectiveness for the final report, the group must negotiate and agree on meeting times and places, allocate research tasks, and prepare a CSR report. These tasks are required, so flexibility is tight and answers are closed (e.g., “Students . . . are required to form their own groups and to select a team leader”). But the tasks are highly interactive and require collaborative processes and agreement (e.g., in selecting the group leader and the administrator). The tasks are interpretative, entailing convergent agreement, reciprocal information exchange, and extensive negotiation. For example, group members have to agree on work allocation and deadlines, pass minutes as a correct record, and plan the report. As the prompt specifies, “Agreed action points for individuals must be explicit.” At the CSR meeting, the first set of minutes and the GSR, including names of group roles, actions taken, and problems faced, are due. These tasks require independent, student-centered learning as the groups must take responsibility and show autonomy.

Task Complexity

Group formation and organization tasks are highly complex across all three task-complexity criteria (see Table 13). This complexity stems from the multiplicity of tasks that need to be identified, understood, negotiated, and allocated to individuals as well as from the systematic minutes that must be recorded on a group-designed form. Students' lack of familiarity with various task aspects -including group processes, conventions, dynamics, and cultural expectations - and their need to schedule the CSR meeting and gather information by the deadline are likely to cause these students to experience considerable communicative stress as they strive to reach consensus.

Table 13.

Task Complexity of Group Formation and Organization

Cognitive complexity	Understand static information on group processes in project prompt and handbook Become aware of cultural expectations and academic conventions of group work and form a group of 5 to 7 students Select a group leader and an administrator Negotiate and agree on meeting times and places Identify task sequence, divide work, and prepare a bid Prepare minutes following specific guidelines
Code complexity	Understand group formation instructions Interpret information and instructions on work allocation and completion dates Interpret information and instructions on the report and CSR meeting
Communicative stress	Become familiar with aspects of the task Identify deadlines and negotiate provisional deadlines Sign up for GSR meeting time Collaboratively prepare CSR for deadline Write minutes following every meeting

Planning the Exhibition

We also examined the nature and complexity of planning the exhibition.

Task Type

After gathering information on exhibitions, the group must design their Reduce IT exhibition by following the specific guidelines in the brief. This task involves designing and managing an exhibition to assist small enterprises “to lessen their environmental impact through improved ‘green computing.’” In terms of interactivity, the task is flexibly tight. Answers and solutions are closed because the prompt stipulates that the Reduce IT exhibition must be divided into three linked zones:

The Energy Reduction Zone

The Resource Reduction Zone

The Travel Reduction Zone

Within these zones, however, interpretation of the design, delivery, and maintenance of the exhibition is more interactive and agreement is convergent. Because the group has to agree on its exhibition design and the Web site and its component features, extensive negotiation is required that involves the group members’ participation in a two-way information exchange. The lecturer explained that challenges include applying green-computing knowledge, creating diagrams and other visuals, inventing hands-on interactive exhibits, and developing a promotional visitors’ guide. The best groups, he stressed, produce models, videos, posters, and handouts.

Task Complexity

As Table 4 shows, the project prompt provides cognitively complex instructions on the various features of the exhibition. In addition, the task presumes familiarity with the concept of an exhibition in order to design the space and the exhibits and plan the work for two staff (see Table 14). In terms of code complexity, explaining the exhibition in an appropriate brochure genre for the typical visitor requires a writing style that is less frequently demanded in university modules. And adhering to the necessary sequences involved in planning the exhibition within the time available will likely cause students to experience communicative stress. Thus, the group negotiations around planning the Web site, promotion, budget, and exhibition brochure render this a highly complex task.

Table 14.

Task Complexity of Planning the Exhibition

Cognitive complexity	Read complex design instructions and synthesize instructions from different sections Design multiple exhibition features Provide job descriptions for two staff Gain familiarity with the design and planning of an exhibition without a model provided
Code complexity	Read and synthesize instructions about writing a brochure explaining the exhibition for visitors Design, write, and promote the Web site using persuasive language
Communicative stress	Plan the exhibition in time available Follow sequence of steps with multiple features Negotiate and agree on Web site, promotion, and budget Gain familiarity with planning a Web site, promotion, and budget Collaborate on preparation of exhibition guide

Preparing for the Final Assessment: Planning and Writing the Report and Preparing the Presentation

In this section, we explored the nature and complexity of developing the report and preparing the presentation.

Task Type

In preparing for the final assessment, the group needs to develop a strategy for writing the report and planning the subsequent presentation. The writing strategy involves collaboratively planning the content, writing, editing, and proofreading the 5,000-word report, following the seven-part report structure that the prompt provides. A collaborative writing strategy, as Ede and Lunsford (1990) have defined it, is a group’s collaborative writing plan, or in Lowry, Curtis, and Lowry’s (2004) terms, it is “a team’s overall approach for coordinating the writing of a collaborative document” (p. 74). This task is tight in terms of flexibility yet both closed and open in terms of answers and solutions in that even though the report must follow a particular format, each group selects the content for their answer. For example, the prompt states, “You should include in this section all information you believe to be relevant.” In terms of interactivity, it is interpretative and requires convergent agreement, two-way information exchange, and extensive negotiation.

In planning and presenting the 8- to 10-minute oral report, the group must agree on presenters, content, and visuals. The preparations require extensive negotiation and therefore considerable interactivity. While initially this task is loose and open, as there are many possible ways to structure the content and prepare the visuals, once preparation is under way, it becomes tight and interpretive, requiring convergent agreement and two-way, optional information exchange.

Task Complexity

The complexity of the report again relates to the cognitive and code complexity of the project prompt, which provides one full page of instructions for the report that are dense and detailed. The outline of the report structure includes an executive summary followed by seven sections, a reference section, and an appendix consisting of four sets of minutes. Each section begins with an instruction (“This section should. . . ”) that states the expectations for the input. For instance, the fourth section, about the exhibition Web site, states, “This section should provide recommendations for the hosting, design, structure, content and maintenance of the website that will accompany your exhibition.” The two recommended readings provide model reports, but these include a final section containing conclusions or recommendations for future studies, which is not part of the project report structure. Following such detailed instructions, agreeing on a shared interpretation, planning the report sections so one section does not dominate, and writing, editing, referencing, and proofreading the report to adhere to the style and deadline constraints are all likely to cause students to experience communicative stress.

The complexity of planning the presentation is also caused by the cognitive and code complexity of the project prompt’s instructions for this crucial final step (see Table 11). For example, the group needs to select presentation content from their written report by following these instructions:

The objective of this presentation is to convince the Project Board why they should select your bid above all others. What you include in the presentation is therefore up to you. However, you are advised that it would be sensible to selectively highlight the key features of your exhibition, Web site, and Web 2.0 strategy and to justify your overall expenditure. You are also advised that trying to cover your whole report within your presentation is almost certainly a very bad idea. The presentation of excessive purchase details is also unlikely to be warranted. Indeed in general, less is likely to be more.

Thus, the group must use this abstract information to determine how to justify their exhibition design, Web site, and budget expenditures in order for their bid to be selected. Additionally, the group must decide who will present and who will cover each content area as well as be familiar with the requirements of academic presentations, such as organizing time, producing slides and the accompanying visuals, synthesizing sections, and checking language. Planning the presentation, which requires attention to detail, and rehearsing for it, which ensures timing, language effectiveness, and more, are both likely to cause students to experience considerable communicative stress (see Table 15).

Table 15.

Task Complexity of Planning and Writing the Report and Preparing the Presentation

Cognitive complexity	Comprehend complex instructions for CSR (including budget, references, and appendix) Sequence multiple features Develop familiarity with executive summary and report writing Read CSR and agree on what to present Agree who will present
Code complexity	Interpret complex instructions on report requirements Interpret instructions on the presentation
Communicative stress	Write report, collaboratively combine sections, edit to meet word limit, and proofread before deadline Develop familiarity of academic presentations Collaboratively plan, structure, and rehearse presentation for deadline Prepare slides, visuals, videos, or models Give presentation

Allocate Marks

In this section, we examine the task type and tax complexity relating to the process of allocating marks.

Task Type

The task of allocating marks is more straightforward in theory than it is in practice because group members have to negotiate and agree on marks based on each individual’s contribution. The group’s minutes document these contributions so the negotiations, and therefore the interactivity, depend on whether this documentation notes any discrepancies regarding individual contributions. If no discrepancies were noted, members received the same mark, but if contributions were unequal, marks would need to vary, and agreement would need to be reached. The prompt states that

The second standing item should be “Allocation of Final Marks.”

Under this you should minute “The group agreed that all members should receive an equal final mark” unless as a group you consider this inappropriate, in which case the current situation should be made explicit.

Task Complexity

The complexity of this task arises from the cognitive and code complexity of the instructions. Students needed to follow these instructions precisely. The process of agreeing on and allocating marks before the final deadline may be stress free or extremely stressful for students, depending on the complexity of the group dynamics.

Discussion

Our analysis of the project prompt has revealed a complex combination of linked tasks, to be completed over a semester, leading to the final assessed report and presentation. We evaluated the expectations of these component tasks using a task-based framework, analyzing each task in terms of type and complexity. Some tasks were more predictable than others, such as the final assignment, which required a written report and an oral presentation. But the exhibition design and implementation is an unusual aspect for a case-study project.

The task-based framework provided an effective way to evaluate each task in terms of task type and complexity. We considered task type in terms of features and levels of interactivity, and task complexity in terms of cognitive complexity, code complexity, and communicative stress. Regarding task type, the features of the tasks usually involved tight flexibility and closed answers and solutions. As a result, the other features of task type frequently showed high levels of interactivity. Because the project involves following fixed expectations, the groups have to negotiate and agree on the interpretation and fulfillment of these expectations, so interactivity is high.

To understand task complexity more fully, we analyzed the project prompt in terms of density, format, structure, and sequencing and found it to be cognitively complex. In addition, we investigated the linguistic features using several readily available software tools: T-unit analysis with SPSS, vocabulary profiler, and concordance. This analysis showed that the language of the prompt was also complex. Because the project prompt had many requirements, and students had much to accomplish before each deadline, we anticipated that they would experience communicative stress.

Regarding code complexity, we conducted a T-unit analysis that identified the project prompt as highly complex—even more complex than the two supplementary readings that it recommends. This finding shows that although the project prompt is designed to mimic related real-world texts, it also conforms to academic style, which tends to employ complex structures and style.

In addition, an analysis of lexical complexity via a vocabulary profiler revealed that a significant proportion of words in the document (more than 75%) hailed from the first 1,000 word families and a low proportion (less than 4%) from the second 1,000 word families. According to Schmitt (2000), the average university student knows 20,000 word families, but Cobb (2009) noted that if second-language learners know the 2,000 most frequently used words of English, then they know 80% of the words in most texts. But he added that many upper intermediate second-language learners have a larger vocabulary that does not include knowing these 2,000 most common words, so they cannot access 80% of the text. In addition, the prompt has a higher than average number of items from the AWL; given that many of the undergraduates are international students (with an International English Language Testing System 7 entry level), the instructions in the project prompt are especially complex and demanding.

The concordance analysis showed that the prompt contained most of the predicted language items, but some occurred more frequently than others did. For example, language relating to the group tasks or group members occurred frequently, but team occurred less frequently, and verbs indicating the need to collaborate, negotiate, and agree while doing the tasks occurred much less frequently. On the other hand, the instructions were precise, frequently using should or must to indicate what groups were obligated to do and often specifying what students should not do. But should is also used in the prompt for advice (e.g., “you should note,” “it should be noted,” or “you should bear in mind”), so students needed to distinguish between the two uses. Thus, to fully understand the lengthy complex prompt, first-year undergraduates would need to read it carefully.

When we compared the project prompt with the two recommended readings using T-unit analysis, we found statistically significant complexity differences between the prompt and recommended readings in terms of both average T-unit length and complexity ratio. The vocabulary profile comparison, on the other hand, showed striking similarities despite the varied formats and the use of diagrams and pictures in the readings. This finding is not surprising because the two recommended readings are business reports rather than academic journal articles. But all three documents show a significantly higher than average AWL count.

All in all, the assignment project prompt is challenging, requiring higher order reading and critical thinking skills that involve analysis, interpretation, inference, and metacognition. The lecturer reported that many students “flip through it” or focus on the assessment section, but they need to read it all carefully to grasp the overall picture as well as the specific instructions and required processes. He also noted that negotiations were often challenging, and some groups had difficulty resolving disputes, which is critical in group work. In terms of communicative stress, many groups were unable to take responsibility and manage the project tasks effectively within the time frame despite the support provided, for example, in the student handbook, which advises students on how to organize their time and work effectively in groups. Minute taking proved challenging for students even though they received specific guidelines, and the division of work within groups often failed to utilize group members’ strengths.

Students were allowed to select their own groups, which does not necessarily create a good mix of skills and experience or ensure a mix of international and native students. Most lecturers either randomly assign students to groups or allow them to self-select, but Chapman, Meuter, Toy, and Wright (2006) showed that the latter, used here, can reduce difficulties. However Shepperd (2011) stressed that ``careful team formation was one of the most important decisions” (p. 364) in undergraduate group projects in order to ensure mixed ability and experience. Despite students often thinking otherwise, Summers and Volet (2008) indicated, culturally diverse groups often perform better together, but Davies (2009) was less certain, noting that studies do not show that a group’s lack of cultural diversity has a detrimental effect on marks.

Group case-study projects in disciplines such as business often mirror real-world tasks in some way, and this investigation has confirmed that the assessed group case-study project in the undergraduate module Computers in Business follows this route. According to the module lecturer, this project was designed to familiarize students with typical projects used at assessment centers and eventually in employment interviews. At an assessment center, students are expected to be able to show a range of competencies, including “team working skills; communication skills; leadership skills; time-management skills; listening skills; motivation and enthusiasm; data analysis skills; decision-making skills; influencing skills; creativity; integrity; and initiative” (Morton-Holmes, 2009). Students needed to exercise such skills for this project, but the prompt document outlining the project tasks was dense and complex, and we had to read it several times in order to unpack and synthesize the information, determine the tasks, and comprehend the chain.

Conclusion

Because prompts for group work projects come in all shapes and sizes, this study provides lecturers with a framework and tools to analyze more fully the complex chain of tasks involved in such projects. This investigation has revealed the complexity of the prompt for a case-study project that was designed to mirror real-world group work projects and to develop the team skills needed for future academic modules within the university as well as an assessment center. Case-study projects not only need to meet these challenges, but, with the increasing number of international students, they need to be accessible linguistically to students from a wide range of linguistic and cultural backgrounds.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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