Socio-Economic Factors and Language Skills
The relationship between socio-economic factors, i.e., parental income, parental education and parental occupation and language skills was also investigated. It was assumed that increases or decreases in parental income, education and occupation are accompanied with parallel increases and decreases in gains in language skills of students. The data presented in Tables 8, 14 and 20 show that the F values pertaining to all these variables obtained through the use of total language skill scores (TLS) were significant at .01 level, thereby rejecting the null hypothesis regarding the relationship between the two sets of variables. Since the sums of ranks of skills (see Table 7a) were significantly different and the correlations among them low and significant the validity of the results by a further analysis pertaining to the relationship of each environmental factor to each skill was warranted. These analyses revealed some interesting trends.

Income : The results presented in Table 8 to 13
TABLE 8:ANALYSIS OF VARIANCE FOR TLS SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36*	730
	X#174.10	179.65	192.17	185.76	169.83	178.62
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	30175.54	7543.88	3.40	P < .01
Within Income groups	725	1607959.06	2217.87
TOTAL	729	168134.60

TABLE 9

ANALYSIS OF VARIANCE FOR LC SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36	730
	X# 30.65	31.92	32.84	33.71	27.28	31.30
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	1139.78	284.95	2.25	N.S.
Within Income groups	725	91999.32	126.90
TOTAL	729	93139.10

TABLE 10

ANALYSIS OF VARIANCE FOR LNC SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36	730
	X# 36.19	38.99	40.87	38.10	33.72	37.69
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	2815.17	712.79	3.64	P < .01
Within Income groups	725	141763.10	195.53
TOTAL	729	144614.27

TABLE 11
ANALYSIS OF VARIANCE FOR GC SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36	730
	X# 54.37	57.87	60.45	62.33	57.72	56.76
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	4390.80	1097.70	4.34	P < .01
Within Income groups	725	183199.80	252.69
TOTAL	729	187590.60

TABLE 12
ANALYSIS OF VARIANCE FOR GC SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36	730
	X# 33.97	34.06	37.94	32.95	34.44	34.57
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	1424.48	356.12	1.54	N.S.
Within Income groups	725	167802.92	231.46
TOTAL	729	169227.40

TABLE 13
ANALYSIS OF VARIANCE FOR EP SCORES FOR STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL INCOMES

Income groups	0-100	101-300	301-600	601-899	900 and above	Total
	N 335	231	107	21	36	730
	X# 18.92	16.81	20.07	18.66	16.66	18.30
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Income groups	4	1011.18	257.79	1.74	N.S.
Within Income groups	725	105330.08	145.28
TOTAL	729	106341.26

show that the F values for LNC and RC only are statistically significant at .05 level. The trend is obviously in the predicted direction for both the skills, except one deviation of the lowest mean achievement score by the group whose parental income was the highest of all. It is quite difficult to explain this deviation. Only one substantial reason can be forwarded that it is the real exception among all these results and unequal numbers in different groups might have some relationship to it. If this deviation is ignored as a stray piece of data, then the results strongly suggest that disparity in incomes of parents is related to the development of LNC and RC. Put differently, the competence of listening and note taking (LNC) and reading comprehension (RC) of low income groups do not seem to have developed as well as of those coming from homes having optimum or high incomes.

Education : The results presented in Tables 14 to 19

TABLE 14

ANALYSIS OF VARIANCE FOR TLS SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educational groups	Illiterate	Primary	High School	College	Post- graduate	Total
	N 170	215	212	102	31	730
	X# 164.54	174.75	184.14	109.61	205.84	167.31
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Parental Education groups	4	81149.40	20299.85	9.43	P < .01
Within Parental Education groups	725	1556935.10	2147.70
TOTAL	729	1638134.50

TABLE 15
ANALYSIS OF VARIANCE FOR LC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educational groups	Illiterate	Primary	High School	College	Post- graduate	Total
	N 170	215	212	102	31	730
	X# 30.40	30.10	32.20	32.59	34.06	31.29
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Parental Education groups	4	1022.22	255.55	2.01	N.S.
Within Parental Education groups	725	92116.88	127.59
TOTAL	729	93199.10

TABLE 16
ANALYSIS OF VARIANCE FOR LNC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educationalgroups	Illiterate	Primary	HighSchool	College	Post-graduate	Total
	N 170	215	212	102	31	730
	X# 33.12	37.02	40.05	40.46	42.16	37.69
Source	df	Sum of squares	Mean square	F	Level of Significance
BetweenParental Educationgroups	4	6240.89	1560.22	8.17	P < .01
Within Parental Education groups	725	138448.76	190.96
TOTAL	729	144689.65

TABLE 17
ANALYSIS OF VARIANCE FOR RC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educational groups	Illiterate	Primary	High School	College	Post- graduate	Total
	N 170	215	212	102	31	730
	X# 50.80	55.57	59.33	61.53	64.45	56.76
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Parental Education groups	4	11873.64	2968.41	12.24	P < .01
Within Parental Education groups	725	115716.96	242.37
TOTAL	729	137590.60

TABLE 18
ANALYSIS OF VARIANCE FOR GC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educational groups	Illiterate	Primary	High School	College	Post- graduate	Total
	N 170	215	212	102	31	730
	X# 31.31	33.86	35.68	36.94	42.06	34.57
Source	df	Sum of squares	Mean square	F	Level of Significance
Between ParentalEducationgroups	4	4433.32	1108.33	4.87	P < .01
Within ParentalEducation groups	725	164794.08	227.30
TOTAL	729	169227.40

TABLE 19
ANALYSIS OF VARIANCE FOR EP SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL EDUCATION

Educationalgroups	Illiterate	Primary	HighSchool	College	Post-graduate	Total
	N 170	215	212	102	31	730
	X# 18.89	18.20	16.87	19.10	23.10	18.30
Source	df	Sum of squares	Mean square	F	Level of Significance
Between ParentalEducationgroups	4	1293.86	323.46	2.23	N.S.
Within ParentalEducation groups	725	105047.40	144.89
TOTAL	729	106341.26

demonstrate the validity of the predictions regarding the relationship between education and language skills. Again the F values for LC and EP are not significant. The significant results for the other skills more clearly evidence the trend stated for income above, meaning thereby that parental education plays a more crucial role in the development of LNC, RC and GC. The results further indicate that illiterate parents or those having meager education perhaps are not of much help to their children and, therefore, these students seem to suffer from this handicap from the pre-school period and this initial disadvantage remains un-bridged later.

Occupation : The trends reported for income and education are reinforced by the data pertaining to occupation presented in Tables 20 to 25.

TABLE 20
ANALYSIS OF VARIANCE FOR TLS SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupationalgroups	Un-skilled	Skilled andSemiskil workers	Businessand white collars	Semi-Profe-ssionals	Profe-ssional	Total
	N 93	179	312	57	89	730
	X# 175.65	170.78	175.63	202.82	192.60	178.63
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupational groups	4	65433.44	16358.36	7.54	P < .01
Within Occupational groups	725	1572701.16	2169.243
TOTAL	729	1638134.60

TABLE 21
ANALYSIS OF VARIANCE FOR LC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupational groups	Un-skilled	Skilled and Semiskilledworkers	Business and white collars	SemiProfe-ssionals	Professional	Total
	N 93	179	312	57	89	730
	X# 30.04	30.76	31.15	34.45	32.18	31.29
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupationalgroups	4	849.44	212.36	1.66	N.S.
Within Occupationalgroups	725	92289.66	127.30
TOTAL	729	93139.10

TABLE 22
ANALYSIS OF VARIANCE FOR LNC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupational groups	Un- skilled	Skilled and Semiskilled workers	Business and white collars	Semi- Profe- ssionals	Profe- ssional	Total
	N 93	179	312	57	89	730
	X# 35.94	36.42	36.49	44.35	42.03	37.69
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupationalgroups	4	5194.83	1298.71	6.75	P < .01
Within Occupationalgroups	725	139419.44	192.30
TOTAL	729	144614.27

TABLE 23
ANALYSIS OF VARIANCE FOR RC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupational groups	Un-skilled	Skilled and Semiskilled workers	Businessand white collars	Semi-Profe- ssionals	Profe-ssional	Total
	N 93	179	312	57	89	730
	X# 53.80	54.59	56.23	65.49	60.54	56.76
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupational groups	4	7577.37	1894.34	7.63	P < .01
Within Occupationalgroups	725	180013.23	248.29
TOTAL	729	187590.60

TABLE 24
ANALYSIS OF VARIANCE FOR GC SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupationalgroups	Un-skilled	Skilled and Semiskilled workers	Businessand white collars	Semi-Profe- ssionals	Profe- ssional	Total
	N 93	179	312	57	89	730
	X# 34.62	32.29	33.95	38.95	38.52	34.57
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupational groups	4	3544.96	886.24	3.89	P < .01
Within Occupational groups	725	165682.44	228.53
TOTAL	729	169227

TABLE 25
ANALYSIS OF VARIANCE FOR EP SCORES OF STUDENTS COMING
FROM HOMES HAVING DIFFERENT PARENTAL OCCUPATION

Occupational groups	Un-skilled	Skilled and Semiskilledworkers	Businessand white collars	Semi-Profe- ssionals	Profe-ssional	Total
	N 93	179	312	57	89	730
	X# 21.25	16.72	17.82	19.58	19.32	18.30
Source	df	Sum of squares	Mean square	F	Level of Significance
Between Occupationalgroups	4	1524.38	381.10	2.64	N.S.
Within Occupationalgroups	725	104816.88	144.56
TOTAL	729	106341.26

It suffices to say that the F values for LC and EP are again not significant, and perhaps other data are not as clear and consistent as they are for education.

Attention needs to be drawn to the rejection of the hypothetical predictions pertaining to LC and EP. As may be recalled, these were found to be the most difficult skills, attaining the 4th and 5th ranks in the hierarchical order of language skills. The data strongly show that inequalities in parental income, educational and occupational status did not seem to have affected the acquisition of these two skills, indicating thereby that their development perhaps is not much prone to environmental influences. Is it because both of them may require a special type of training for their cultivation, as ordinary Indian homes lack such an environment? Another interpretation seems feasible for LC. Opportunities for manipulating audile verbal symbols for people from different strata of society are more or less similar and, consequently, disparity in the development of skills may not be as wide as that found for the other skills. On the contrary, opportunities for handling materials and as a result of it for manipulating visual verbal symbols in different strata of society vary from having no opportunity at all to being constantly busy handling and manipulating these symbols only. That is perhaps why RC has shown a clearer evidence of proneness to environmental influences than the other language skills.

SEX AND LANGUAGE SKILLS

The hypothesis that the language skills of boys and girls differ was tested through t tests for each skill independently as well as by using TLS. These data reported in Tables 26 to 31 show that

TABLE 26
t TESTS FOR TLS SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	173.72	3.19	P < .005
Girls	320	184.93

TABLE 27
t TESTS FOR LC SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	30.41	2.26	P < .025
Girls	320	32.43

TABLE 28
t TESTS FOR LNC SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	36.25	3.15	P < .005
Girls	320	39.54

TABLE 29
t TESTS FOR RC SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	55.42	2.56	P < .025
Girls	320	58.48

TABLE 30
t TESTS FOR GC SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	32.34	4.52	P < .0005
Girls	320	37.43

TABLE 31
t TESTS FOR EP SCORES OF BOYS AND GIRLS

Sex	N	Mean	t	Level of Significance
Boys	410	19.29	2.48	P < .01
Girls	320	17.05

all the t values are significant beyond .025 levels of significance, thereby accepting the conceptual predictions about the relationship between sex and language skills. The data clearly show that girls are superior to boys in all the skills except EP. This finding is in line with many such findings regarding developmental factors related to sex such as physical and mental maturity, verbal intelligence, etc. This is perhaps one of the important reasons why girls are generally found superior to boys in academic achievement. Since it has been shown that the gains in language skills were related to the gain in academic achievement, it is easy to explain why girls and students coming from homes with high socio-economic status are found superior to their counterparts, the reason being their superiority in language skills. That language development for human learning (or conceptual learning) is the most vital and crucial factor is very strongly vindicated by the entire data obtained through this project.