Impact of Cultural and Language Background on Learning Computer Science Concepts

Ismat Aldmour Department of Computer Science and Engineering

Al-Baha University Al-Baha, Saudi Arabia

e-mail: iaaldmour@bu.edu.sa

Aletta Nylén Department of Information Technology

Uppsala University Uppsala, Sweden

e-mail: aletta.nylen@it.uu.se

Abstract— Computer science terminology is generally based on words that have a related original meaning in English and rooted in western tradition. Hence, students from other cultures and students that are not native English speakers, will not be helped by language and culture in understanding computer science concepts. In this work, the authors review the interrelationship between language, cultural background, and the learning of computer science. A comparative study is under preparation in which this relationship is to be examined. The study will compare the intuitive understanding of computer science concepts between Saudi student groups of different English language proficiency levels and of different maturity levels. A test has been designed in order to reveal differences in the perception of computer science concepts that can be attributed to such background differences. The study will serve as a starting point for further work on how computer science education can be enhanced for students that are non-native English speakers.

Keywords- computer science education; language transfer; cultural diversity;

I. INTRODUCTION In Saudi Arabia, most computer science students that

enter the university meet studies that are entirely in English for the first time. They have studied computer literacy in secondary school and are familiar with some basic computing terminology, but these studies are conducted in Arabic, not in English. To prepare the students for this transition, in their first year, they are offered two intensive general English courses and a specialized one for their own field of study. In this work, we are investigating if there is a connection between proficiency in English and the corresponding culture, and the intuitive understanding of computer science terms and concepts. If there is such a connection, a deeper understanding of its nature could form a basis for designing courses in English that are specially suited for enhancing learning in computer science.

The work is interesting for teachers in parts of the world where the students’ exposure to the English language and to the corresponding culture is low, e.g. in Saudi Arabia. It also has a more general interest since any student may be unfamiliar with the meaning of an English word that constitutes a term in computer science. Understanding the relation between proficiency in English and learning

computer science terms can be used to enhance computer science education.

In the next section we will discuss the background of this work in progress. Section III gives an overview of the test and Section IV presents the computer science terms occurring in the test. In Section V we describe the intended use of the test and how the results will be analyzed. Conclusions are made in the last section.

II. BACKGROUND In his book Culture and organization: software of the

mind: international cooperation and its importance for survival [1], Hofstede describes culture as being “the collective programming of the mind which distinguishes the members of one group or category of people from another”, that it is a collective phenomenon shared among people living in the same social environment. Pavlenko [2] states that individuals acquire and assess concepts through language and that such language based concepts are social, i.e. they require that members of a particular speech community are in agreement in order to achieve an amount of shared understanding in communication around an activity. People sharing the same culture and language also have a shared understanding of language based concepts. “The words and expressions associated by NCS [Native Chinese Speakers] convey Chinese culture, and those associated by NES [Native English Speakers] convey English culture” [3].

This work only deals with the aspects of culture that are visible in the language. When we discuss understanding a specific word, this also includes familiarity with the culture and lifestyle aspects that impact subtle meanings of words and how they are used. English is the first language in many different countries with differences in culture. In this work, when referring to the culture corresponding to English, we concentrate on what is common in these cultures when viewed by a foreign computer science learner, e.g. an Arabic learner.

Computer science terminology generally originates in English. Terms and concepts are English words for more or less similar or related phenomena, e.g. handshaking, protocol, and piggybacking. For distinction purposes, in this work, word is used to denote the everyday usage, while term is used to denote the computer science usage of a word. Most course literature is written in English and commonly utilizes

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DOI 10.1109/LaTiCE.2014.15

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Table 1: Computer science (CS) terms used in the test and the concepts they are connected to.

the readers’ familiarity with the corresponding culture in examples aimed at giving the reader an intuitive understanding when learning new concepts.

In [4], the authors investigate whether the origin of technical terms influences the mental representation of the terms in students. They find that students find technical terms in everyday language more easily defined, more familiar and more accessible than terms originating in foreign languages. For a student, not native in English, all terms are foreign, hence it is reasonable to assume that learning computer science terms will require more work than for students who are native English speakers.

In the field of second language acquisition (SLA), language transfer is a concept used to describe that when a new language is learned there is an influence from previously known languages [5]. This influence can be either positive, i.e. it makes learning new vocabulary easier, or negative. Susan Gass [6] explains transfer, and its significance in learning vocabulary, by giving a historical overview of how the view of transfer has changed over the years. She starts by citing Lado’s book from 1957 [7]:

... individuals tend to transfer the forms and meaning and the distribution of forms and meanings of their native language and culture to the foreign language and culture—both productively when attempting to speak and to act in the culture, and receptively when attempting to grasp and understand the language and the culture as practiced by natives. She explains that a more modern view is that of Ard and Homburg [8] where they propose that transfer should be viewed more as a facilitator of learning than as a direct imposition of native language forms and meanings.

In this work, we seek to investigate whether the students’ proficiency in English and its culture influence their intuitive understanding of computer science concepts, i.e. if there is a transfer, similar to that in SLA, from languages that the students know to the intuitive understanding of computer

science concepts, which we will call Language to Computer Science (L-CS) transfer.

We present a test, designed to test the students’ intuitive understanding of central concepts in computer science. The test is to be used on students with little knowledge in computer science, so that the understanding that they show on the test is attributed to their understanding of the words based on their language background. The test builds on ideas similar to [9], where language transfer was investigated by subjecting students to a test where their understanding of a previously unknown language was tested. In that case, the authors concluded that language transfer does take place and the extent of transfer is influenced by the students’ age, number of previously known languages, years in school, and intelligence (IQ).

III. OVERVIEW OF THE TEST We have designed the test with the purpose of detecting

whether knowledge of English results in a positive transfer to Saudi students’ ability to get meanings from unfamiliar computer science terms and concepts. Specifically, to test the ability to infer meanings and usages of terms which are of bi-use in both everyday English and in computer science. One of the results from [9], which is also reported in [5], is that maturity, both in age and in the extent of previous studies, has an impact on language transfer. It is therefore reasonable to assume that maturity is a factor also in L-CS transfer. The test will be used to investigate the occurrence of L-CS transfer and the impact of maturity on the transfer. Groups of Saudi students at two different levels of maturity and at two different levels of proficiency in English, all with little knowledge in computer science, will be compared.

The test consists of two parts. In the first part, the students provide general information about themselves such as age, field of study, and year of study. They also assess the level of their knowledge in computer science and provide

# CS concept CS term # CS concept CS term

1 Problem --- 9 Language Procedural, Syntax

2 Data Abstraction, Encapsulation, Representation, Validation, Verification

10 Communication Protocol

3 Computer Logic, Proxy 11 Software Analysis, Interface

4 Test Reliability 12 Program Code, Control

5 Algorithm Aloha, Piggybacking, Round-Robin

13 Computation ---

6 Process Batch, Bootstrapping, Pipelining, Sampling

14 Structure Substrate

7 System Combinational, Embedded, Timesharing

15 Model Imperative, Simulation, Synthesis

8 Information Non-repudiation

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information about any prior computer science training. This makes it possible to exclude students with prior special knowledge in computer science. In this part, the students also provide information about their level of proficiency in English. This is to ensure that all students fit the general profile of their respective group.

The second part of the test assesses the students' understanding of English terms, both in their everyday use and in their use as computer science terms. Since the students are not expected to have knowledge in computer science, they are asked to use their intuitive understanding of the word to infer the computer science meaning.

IV. TERMS OCCURRING IN THE TEST 30 terms are used in the test. Each term can be linked to

one of the 15 basic concepts in computer science as classified by Zendler and Spannagel [10], namely: problem, data, computer, test, algorithm, process, system, information, language, communication, software, program, computation, structure, and model. Table 1 lists these 30 terms together with the concepts that they can be linked with. For each term, the student is given the first translation shown by Google Translate (translate.google.com). The translation is given because we assume that the student will use some kind of quick translator in his studies, however, such a translation is not likely to be of much help in getting the many everyday meanings of the term.

For each term, there are two columns, one for the everyday meanings and one for the computer science meanings. Four different options of related meanings of the term are given in each column. The student is asked to tick the correct answers from the four options, of which two per column are correct.

The terms that are used in the test are purposefully chosen to be of bi-use nature. Each term has a computer science meaning whilst it has an everyday meaning related to the computer science meaning. For example, the term validation means, in everyday language, an “act, a process, or an instance of validating” [11], e.g. to validate certificates for authenticity, measuring devices for accuracy and social validation. In computer science the term validation is linked to the basic concept data whereby data validation is the process of making sure that the data are of proper format and size to be valid as input. Hence, the everyday use of validation (as to inspect with reference) with the concept of things or subjects (devices, certificates, people) has been

extended to support the handling of the concept of data (inspect with reference to certain data format) in computer science.

Table 2 shows an example of how the term validation appears in the test. There are four different options in each column below the two questions. In the table, the correct answers have been marked with ticks.

V. APPLYING THE TEST The test will be applied on students of Al-Baha

University in Saudi Arabia. Colleagues in the field of computer science education will referee both the test and the selection of terms used in the test before it is being applied. First, the test will be applied on a smaller group of students for validity and stability purposes and to ensure that the level of difficulty is appropriate. After adjustments, the test will be applied to three different groups of students defined as follows:

Group 1: a group of final year students in any area other than English and computer science, who study mainly in Arabic.

Group 2: a group of English literature students in their final year of studies.

Group 3: a group of first year students who only know English as a second language at a secondary school level.

Students in Group 2 are expected to have significantly more knowledge of English than the other two groups. They are considered to be at the Proficient level, while students in group 1 and group 3 are considered to be at the Primitive level. Any significant difference the test reveals between group 1 and group 2 that is favoring group 2 could be attributed to their higher knowledge level of English and could be an evidence of L-CS transfer.

Also, students in group 1 and group 2 (Senior level) are expected to be more mature than students of group 3 (Beginner level). The purpose of testing group 3 is to compare their results to those of group 1 to be able to investigate the impact of maturity on L-CS transfer.

The three groups will be compared with regard both to their ability to discern meanings of the words in everyday English, and their ability to infer their meanings as terms in computer science. An analysis of the distribution of the results of the completed tests will give an insight to the questions of the study. For example, if the final year English literature students are significantly more successful in inferring meanings of computer science terms than the other

Table 2: Example of a question from the test.

- Choose the meanings (left col.) that comes to mind of the term "Validation" (����� �� ����) in normal English.

and choose (right col.) meanings of "Validation" in comp. science used with concept of (� ������ ) Data

Making sure that the product satisfies the needs of the consumers

To inspect the suitability of data before being entered to the computer program

Medical Examination Converting data from one form into another

Inspecting the correctness of academic certificates. Sending the data to the computer program

Account inquiry To reject no numeric entries into the grades field in school grades software

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two groups, we have reason to believe that being knowledgeable in English makes acquiring computer science concepts easier. A comparison of the results of final year students studying mainly in Arabic and first year students, assesses the impact of maturity L-CS transfer.

Since the students who will be tested are knowledgeable in Arabic, it is reasonable to assume that L-CS transfer, positive or negative, from Arabic, will influence the results. By excluding students with special knowledge in Arabic, students in Arabic literature, we can assume that the impact of L-CS transfer from Arabic affects all groups equally. To be able to generalize the results, further testing on student groups with different backgrounds is needed.

VI. CONCLUSION This is an article describing work in progress. In second

language acquisition, positive or negative transfer from previously known languages to unfamiliar languages occurs, resulting in either facilitating or degrading the acquisition. In this work the authors extend the idea of language transfer to the possibility of transfer from language knowledge to computer science understanding, L-CS transfer.

For this purpose, we present a test, with a number of terms that are of bi-use in everyday English and in computer science. The test investigates the association between understanding the everyday meanings of words and their meanings as computer science terms. The test is to be applied on groups of students at Al-Baha University in Saudi Arabia, who are not knowledgeable in computer science, and who vary in English proficiency and maturity levels. Conclusions about transfer from knowledge of English to understanding computer science terms and the impact of maturity on this transfer are to be made upon analyzing and comparing the results.

If there is a connection between proficiency in English and intuitive understanding of computer science concepts, a deeper understanding of its nature could form a basis for designing courses in English that are specially suited for enhancing learning in computer science. More insight could be gained by comparing achievement in early computer science courses of student groups taught English the traditional way to groups more subjected to English words that constitute computer science terms.

We strongly believe that the results of this study, when completed, can be of importance to general computer science education directed towards students who are non-native English speakers as well as providing insights into how English courses, preparing for computer science studies, can be designed.

ACKNOWLEDGMENT This joint work was possible due to the cooperation

between the International Science Program (ISP) at Uppsala University and Al-Baha University.

REFERENCES

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[6] S.M. Gass, "Second language vocabulary acquisition," Annual Review of Applied Linguistics, vol. 9, pp. 92-106, 1988.

[7] R Lado, Linguistics across cultures. Ann Arbor, Michigan: University of Michigan Press, 1957.

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[10] A. Zendler and C. Spannagel, "Empirical foundation of central concepts for computer science education," ACM Journal of Educational Resources in Computing, vol. 8, no. 2, June 2008.

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