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ABSTRACT
Language is a critical factor in education, which determines learner's performance in school and out of school. The environment in classroom and in industry or work is linguistically as well as culturally diverse in Indian contexts. Is there a correlation between proficiency in language attained at school, and skills in language required to acquire work specific product oriented knowledge? With the implementation of States' language policy taking a front seat, is there any change taking place in language performance and language competence required in school as well as in work place? In an officially trilingual country, the English-only scene is giving place to a combination of English and Indian languages in areas where English once held a high position.
This paper presents results of an experiment conducted in a High Tech Industry, located in Mysore. Content of the try out was a text, taken from a training manual, for a new product that the employees were not familiar with. In understanding and discussing the dimensions of producing the new artifact, my analysis points to the pre-dominance of employees' culture language (home language) and functional English rather than only English.
Key Concepts
Knowledge, job specific content, linguistically diverse high technology, industrial environment, culture language (state dominant language), functional language (English).
BACKGROUND
Language use in India in the industrial sector is defined by the end product of the Organization. The range of language used spans from the local to the international, in small and large scale industries. In fact, use of language in the industrial setting is structured in a hierarchical manner. English is at the peak of the triangle at the written level, where culture language does yet not fit the bill, and the local language makes the base line at the oral level. The State's Language Policy as well as advances in Science and Technology has triggered an awareness of status and function of culture languages in the domains of education, administration and mass communication.
This paper discusses changes occurring in communicative ability in English versus the culture language to express ideas, concepts, knowledge, and understanding. Limited self-expression in English inhibits free flow of interaction, thus forcing an access to home language skills to gain knowledge. Employees use their cultural knowledge and inherited language skills to improve their interactive abilities.
Knowledge is the body of truth, of information and principles, philosophies and ideologies, acquired, interpreted and rediscovered by humankind. Such dimensions are required to develop skills and job concepts. In the industrial world, knowledge is interpreted as job specific content or information, which a person gains through training, learning, and experience.
In most of the high technology industrial environments, knowledge of product and process has to be passed onto the new employees through training in a classroom setup as well as hands on method. The knowledge is somewhat available in written form but verbal discussions need to take place between persons of varying skill levels to absorb the concepts and information. The written form, in most cases in India, is in English language whereas the employees come from a variety of different home and school language groups. They might have done some years of college or technical education in English medium but in most cases they are not very competent in the use of English language.
In such multilingual situations, it becomes an interesting issue as to what language to use to transfer information and knowledge of high technology. Should it be in English, in local language, or a mixture?
EXPERIMENT
This problem is addressed here using an experimental approach to find out the effect of language use on knowledge in an industry having a multilingual work force.
The industry in which this experiment was conducted had recently purchased a new high speed automatic machine from USA, which can be used to make different precise shapes and forms from wire raw materials. Such machines are quite rare in India, and so such experience, knowledge and training is not available.
A training book titled Slide Forming Concepts Manual was obtained to educate the work force. The manual is written in English language and is highly technical in nature. The industry identified 9 persons who needed to be educated using this manual in which 3 were seniors and 6 were juniors.
METHODOLOGY
For the purpose of this experiment, following methodology was used:
- The group was divided into 2 subgroups by drawing lots; each group of 4 to 5 having 1to 2 seniors and 3 juniors.
- Each group was to work separately - one using strictly English language and the other using Kinglish (Code switching and code mixing between Kannada and English).
- Each group was asked to study Chapter 1 of the manual and discuss/learn the contents in the language assigned to them for a fixed duration (say 3 or 4 hours). The verbal interaction was audio taped for later analysis.
- At the end of the learning period, each person was given a test paper. Answers to the questions showed how well the knowledge had been acquired. Marking of the answer sheets was done to put numerical value on knowledge obtained.
- A joint training session in Kinglish was then held to ensure that all persons have understood Chapter 1.
- After studying the first Chapter, each group was asked to study Chapter 2 but they were asked to use the other language, that is, the group that used English previously would use Kinglish now to study the second chapter, and the group that used Kinglish would use only English to study the second chapter.
- A Test was conducted after Chapter 2 to gauge the extent of knowledge gained. (Similar to step 4 above.)
- A joint session was held to explain Chapter 2 well to everybody. (Similar to step 5 above).
- The steps from 1 to 8 were considered as Round - 1.
- For Round - 2, lots were drawn up again and 2 fresh subgroups were formed randomly. (Similar to step 1 above.)
- Steps 1 to 8 were repeated with Chapters 3 and 4 (Similar to Chapters 1 and 2 above).
- After the completion of Round - 2, results from these experiments were compiled and analyzed.
DATA
Background information of the participants (Age, Qualifications, Years of Experience, Medium of instruction in school and post-school, mother tongue, language proficiency and average percent marks obtained in tests are tabulated in Table - 1. See below.
Percentile marks obtained in experimental tests, chapterwise, languagewise, individual average and group average are given in Table - 2. See below.
ANALYSIS
Looking at Table -2, it is observed that the group average for chapter - 1 is marginally higher for English as compared to Kinglish. But for the rest of the 3 chapters as well as consolidated figures, group averages are higher when Kinglish was used as compared to English.
Comparing individual averages between Kinglish and English, in Table - 1, it is observed that 3 participants obtained higher averages in English. To find out the possible factors contributing to this phenomenon, correlations were made between the background attributes and the average percent marks obtained. The indications are that the Rural / Urban spread and Educational qualification contributed significantly to language variance and acquisition of knowledge.( Refer Table - 3 and Table - 4, see below).
CONCLUSION
This is a novel experiment used to measure the effect of language use on knowledge in a high technology industrial setup. Even though the sample size was small, it does point out that the use of local language facilitates the learning process. Further investigations, using larger and more homogenous participants, would throw further light on the subject.
REFERENCES
1. www.iteawww.org/TAA/glossary.htm December 6, 2004.
2. Personal Discussion with Prof. Akshay Rao, Department of Management Studies, University of Minnesota, Minneapolis, USA. December 28, 2003 at the Central Institute of Indian Languages, Mysore.
3. 1997. Slide Forming Concepts Manual. Spring Manufacturers Institute Educational Foundation and the Precision Metal Forming Association. USA.
TABLES
Table - 1
Background Information and Average Percent Marks Obtained
Name
Age
Qualifi-
Years
Rural/
Medium
Medium
Mother
Lg
Average
Average
Yrs
cation
Exper
Urban
School
Post-Sch
Tounge
Rd, Wr, Sp
English
Kinglish
Mr. Venugopal
20
Dip(Mech)
1
U
K
E
K
E, K, H, S
76.5
60.5
Mr. Dayanand
24
Dip(Mech)
1
R
K
E
K
E,K
53.7
84.6
Mr. Harish
24
Dip (Tool)
2
U
E
E
K
E, K ,H
72.9
77.4
Mr. Nagaraj
25
Dip (Mech)
5
R
E
E
K
E, K, H
66.9
76.6
Mr. Sridhar
26
Dip(Mech)
2
R
K
E
K
E,K
72.1
77.4
Mr. Richards
27
Dip(Mech)
5
R
E
E
K
E, K, M, U, H
84.8
86.1
Mr. Vishwanath
29
B.E (Mech)
5
R
K
E
K
E, K, H
82.1
92.2
Mr. Raghu
38
Dip (Tool)
16
U
K
E
K
E, K, H, V, S
82.5
78.2
Mr. Chengappa
54
B.E (Met)
25
R
K
E
C
E, K, H, C, T
92.3
78.5
Average
74.9
79.0
C=Kodava; E=English; H=Hindi; K=Kannada; M=Malayalam; S=Sanskrit; T=Tamil; U=Telugu, V=Marathi
Table - 2
Percent Marks Obtained in each Chapter
Name
Age
Qualifi-
Eng
King
English
Kinglish
English
Kinglish
English
Kinglish
Yrs
cation
-1
-1
-2
-2
-3
-3
-4
-4
Mr. Venugopal
20
Dip(Mech)
76.5
52.5
68.4
Mr. Dayanand
24
Dip(Mech)
60.0
84.6
47.4
Mr. Harish
24
Dip (Tool)
70.6
65.0
80.8
84.2
Mr. Nagaraj
25
Dip (Mech)
70.6
72.5
80.8
63.2
Mr. Sridhar
26
Dip(Mech)
70.6
75.0
69.2
84.2
Mr. Richards
27
Dip(Mech)
85.3
87.5
84.6
84.2
Mr. Vishwanath
29
B.E (Mech)
88.2
80.0
96.2
84.2
Mr. Raghu
38
Dip (Tool)
76.5
77.5
88.5
78.9
Mr. Chengappa
54
B.E (Met)
76.5
80.0
92.3
78.9
Average
77.2
76.5
70.0
74.0
82.7
86.5
69.7
78.9
Table - 3
Results sorted by Rural / Urban Spread
Name
Age
Qualifi-
Years
Rural/
Medium
Medium
Mother
Lg
Average
Average
Yrs
cation
Exper.
Urban
School
Post-Sch
Tounge
Rd, Wr, Sp
English
Kinglish
Mr. Dayanand
24
Dip(Mech)
1
R
K
E
K
E,K
53.7
84.6
Mr. Nagaraj
25
Dip (Mech)
5
R
E
E
K
E, K, H
66.9
76.6
Mr. Sridhar
26
Dip(Mech)
2
R
K
E
K
E,K
72.1
77.4
Mr. Richards
27
Dip(Mech)
5
R
E
E
K
E, K, M, U, H
84.8
86.1
Mr. Vishwanath
29
B.E (Mech)
5
R
K
E
K
E, K, H
82.1
92.2
Mr. Chengappa
54
B.E (Met)
25
R
K
E
C
E, K, H, C, T
92.3
78.5
Average of Rural Participants
75.3
82.6
Mr. Venugopal
20
Dip(Mech)
1
U
K
E
K
E, K, H, S
76.5
60.5
Mr. Harish
24
Dip (Tool)
2
U
E
E
K
E, K ,H
72.9
77.4
Mr. Raghu
38
Dip (Tool)
16
U
K
E
K
E, K, H, V, S
82.5
78.2
Average of Urban Participants
77.3
72.0
Table - 4
Results sorted by Educational Qualification
Name
Age
Qualifi-
Years
Rural/
Medium
Medium
Mother
Lg
Average
Average
Yrs
cation
Exper.
Urban
School
Post-Sch
Tounge
Rd, Wr, Sp
English
Kinglish
Mr. Vishwanath
29
B.E (Mech)
5
R
K
E
K
E, K, H
82.1
92.2
Mr. Chengappa
54
B.E (Met)
25
R
K
E
C
E, K, H, C, T
92.3
78.5
Average of Participants with Degree
87.2
85.3
Mr. Nagaraj
25
Dip (Mech)
5
R
E
E
K
E, K, H
66.9
76.6
Mr. Harish
24
Dip (Tool)
2
U
E
E
K
E, K ,H
72.9
77.4
Mr. Raghu
38
Dip (Tool)
16
U
K
E
K
E, K, H, V, S
82.5
78.2
Mr. Venugopal
20
Dip(Mech)
1
U
K
E
K
E, K, H, S
76.5
60.5
Mr. Dayanand
24
Dip(Mech)
1
R
K
E
K
E,K
53.7
84.6
Mr. Sridhar
26
Dip(Mech)
2
R
K
E
K
E,K
72.1
77.4
Mr. Richards
27
Dip(Mech)
5
R
E
E
K
E, K, M, U, H
84.8
86.1
Average of Participants with Diploma
84.9
90.1
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