1. Introduction
Many linguists and dialectologists have found that languages and dialects change over time. The changes can occur at many levels, e.g. syntax, vocabulary, pronunciation and so on. At the vocabulary level, words change over time due to many reasons. Borrowing and innovation of words are the most important reasons. On the one hand, words might be borrowed when there is direct contact with people who speak other languages (Ahangari and Moradi, 2013) or dialects. On the other hand, people innovate by incorporating new words into their own languages as a feature of languages in general (Brooks and Kempe, 2014). As a result, languages change over time, leading to differences in the words used by older and younger generations. Such differences are the result of many sociological factors such as age, gender, education, social class, etc. Labov (1966) investigated the age factor in a study he conducted on New Yorkers, using age as a social factor. Gender is another important factor that plays a significant role in lexical change within the same language or dialect over the years. Since languages are always changing (Peirce, 1995) and evolving, it has been noticed that many words are rarely or never used nowadays because they have been replaced with new ones. New generations use words different from those used by old generations. This may lead to communication difficulties between the two generations. It may cause the loss of old words as well.
It has been noticed that there are differences between the vocabulary used by older and younger generations in the Jizani dialects. For instance, the older generation calls “coal” as [bxʃ], however, the younger generation calls it [fħm]. Hence, this study was concerned with the lexical gap in the Jizani dialect between the two generations. In addition, it explored the reasons for the differences between old and new words.
2. Literature review
Lexical change is a natural linguistic phenomenon. Changes are grouped into innovating a new meaning, changing the meaning or losing the meaning (McMahon, 1994). These changes are due to many factors, such as the influence of other languages and dialects. Khaldun and Rosenthal (1967) indicated that the lexical changes that happened to the Arabic dialects in the East were the result of language contact with Persian and Turkish people. This kind of communication resulted in having many borrowed words from the two languages. Ahangari and Moradi (2013) presented many examples of borrowed words from Persian to Arabic because of direct contact during trade exchanges in the past.
Several studies in the field of sociolinguistics have dealt with changes in languages. Lexical change is of interest to many sociolinguists. Grondelaers and Geeraerts (2009) studied lexical variation and change due to sociolinguistic factors using corpus-based data. Social factors, such as “social class, age, race, religion and other factors” (Trudgill, 2000, p. 24) can cause language and dialect changes, including lexical ones (Bordin, 2009; Saladino, 1990; Sharma and Sankaran, 2011).
“Age differences are a common tool for detecting linguistic change” (Nagy, 2011, p. 370). As a sociolinguistic variable, age has been explained in detail by Eckert (1997), who divided the age variable according to its use into historical change and age grading. White et al. (2018) found that there is a difference between older and younger speakers in their judgements on concrete nouns. Younger speakers depend heavily on new materials such as plastic, while older people relied more on traditional materials such as glass in categorizing household containers. Moreover, Nagy (2011) argued that the differences between younger and older speakers are not huge within four generations. In contrast, Banagbanag (2018) stated that because of the huge age gap, there is a significant difference between old and young generations. Muttaqin et al. (2019) reported that old Indonesian people speak formally, while young people speak differently, mixing other dialects or involving code-mixing and switching as a reflection of their social status. The different styles preferred in communication between generations can cause this kind of change. The millennial generation prefers texting to communicating verbally face to face, as their grandparents would (Downs, 2019). It was found that “Lexical differences found [between ages] contain some expressions to illustrate first person singular (I), third singular person (He/She), demonstrative (that), quantifier (few), and verb (go)” (Muttaqin et al., 2019, p. 52). Since linguistic differences may be used to recognise different groups (Trudgill, 2000), younger speakers may embrace such differences and changes (Belahcen and Ouahmiche, 2017) as a way to indicate their social identities.
The age factor might result in vocabulary loss. In his study, Bordin (2009) found that younger people had not heard certain Inuktitut terms, while old people recognised them even though they hardly used them. He also found that word loss included words and phrases with meanings that were irrelevant to a specific speech community or generation. Among Inabaknon speakers, some words were known only by old people, some only by middle-aged people and some only by young people (Banagbanag, 2018). This ensured that there was a lexical gap between generations.
Chambers and Schilling (2018) stated that linguistic variation can be anticipated by gender. Hocini (2011) found in his study that women like to use cross-cultural terms in their speech, while men prefer using local ones. Females innovate linguistic changes (Labov, 1990), including lexical ones. Labov (1972) also argued that women use the postvocalic/r/more than men do in all situations and across different age groups. Al-Qahtani (2015) and Al-Wer (1991) argue that young females are mostly responsible for linguistic change, while males and older females have little effect on that.
Investigating lexical variation and change in relation to age in Saudi Arabian dialects, in general, and in the Jizani dialect, in particular, has drawn little attention. A few studies have been conducted on Saudi dialects (Al-Bohnayya, 2019; AlAmmar, 2017; Al-Qahtani, 2015; Hind, 2019; Hussain, 2017) and the Jizani dialect (Alfaifi, 2021; Alfaifi and Behnstedt, 2010; Davis and Alfaifi, 2019; Hamdi, 2015; Lowry, 2021); however, to the best of my knowledge, there are no studies on the lexical differences between old and new generations in this dialect. Therefore, this study aimed to bridge this gap by exploring the lexical differences between the old and new generations and the reasons for this gap.
3. Research questions
Is there a lexical gap in the Jizani dialect between the old and new generations?
Does gender affect the lexical gap between the old and new generations?
What are the reasons for the lexical gap in the Jizani dialect between the old and new generations?
4. Methodology
4.1 Method
This study employed a mixed methodology. The data collected from the questionnaire to answer the first research question were quantitatively analysed. The SPSS software was used for descriptive and inferential statistics to compare the lexical gap between the two generations. Additionally, it was used to assess the reliability and validity of the instrument. The qualitative data gathered through interviewing the participants were coded and then analysed and interpreted. Because of the abundance of dialects in the area, this study was conducted on the southern coast of Jazan (from Muzherah to Alarooj village). The questionnaire was sent using WhatsApp groups. Some of the participants were visited and interviewed at home, while the rest were interviewed by phone.
4.2 Sample
Hatch and Lazaraton (1991) suggested that the sample for quantitative data analysis should not be less than 30 participants. In this study, the researcher employed 104 participants, distributed as shown in Table 1. The distribution of the participants was done according to their age, as follows: young participants were 15–30 and old participants were 50+. People aged 31–49 were excluded since they may have known both lexical words, which might have affected the reliability and validity of the results. The participants were randomly surveyed using WhatsApp. A convenience sample was chosen for the interview. There were 12 participants divided by age and gender (3 old males, 3 old females, 3 young males and 3 young females). They were chosen from among the researcher’s relatives and friends. The people who participated in the study spoke the same dialect.
4.3 Research instruments
For the first and second questions, the sample was sent a questionnaire (Appendix). It was a mixture of old and new lexicons, totalling 20 questions. The questions were written in Arabic. The first 10 questions were old words for participants from the new generation and the other 10 questions were new words intended for participants from the old generation. The words used in this study were carefully selected. They are about things or actions that were used in the past and are still used today. The new and old words used in the questionnaire were decided after asking a number of old and young people about their meanings. The researcher made sure that the old lexicon was well known to the older generation and the opposite for the younger generation. The questionnaire aimed to determine if a lexical gap existed between the two groups, and how big it was. The reliability of the questionnaire scored an overall Cronbach’s alpha value of 0.741. The Cronbach’s alpha values for the old generation questionnaire and the new generation questionnaire were 0.756 and 0.507, respectively, as shown in Table 2. This indicates that the questionnaire remained constant if the same one was distributed many times to the same sample members.
To answer the third question, a semi-structured interview was conducted with a convenience sample taken from the same participants (Appendix).
5. Results
The findings were divided into two types: qualitative and quantitative. Each type was analysed separately. To answer the first two questions, I used the quantitative analysis of the questionnaire.
The descriptive statistics including mean, t-test and p-value are shown in Table 3. The mean score for the old generation was 3.588 and 5.208 for the new generation. The independent sample t-test score (t = −3.221, p = 0.002 < 0.01) showed that there was a statistically significant difference between the average scores of the old and new generations. The effect size of the scores of the two groups was 0.31584504, between 0.20 and 0.50, which means it was small.
Furthermore, the results outlined in Table 4 show that the majority of the old generation’s answers were inaccurate. Whereas in Table 5, the descriptive statistics show that the new generation’s correct and incorrect answers were approximately the same.
However, the statistical analysis of the difference between young males and females according to their responses to the questionnaire showed that young males scored a mean of 6.045 which was higher than that scored by young females (4.613). As Table 6 shows, the independent t-test score (t = 2.846, p = 0.006 < 0.01) indicated that there was a statistically significant difference between the average scores of young males and females. The effect size was also small (0.27907326).
The analysis of the qualitative data gathered from the interviews to answer the third question showed that the average time the older generation consumed on social media was 0.83 h per day. The average time they spent with the younger generation – usually relatives – was 8 h a day. On the other hand, younger speakers reported that they consumed about 5.16 h on social media every day. The time they sat with the older generation was about 2.16 h. The average time young males spent with the older generation was 1.33 h, which was almost half of what the young females reported (3 h a day). Young males spent about 4.33 h spent using social media, whereas about 6 h was the average time young females consumed every day using social media. Table 7 shows the difference between young males and females in terms of the time they spent on social media and with older people. Older participants all agreed that the reason for the linguistic gap is technology, especially smartphones. Lastly, the answers for the younger generation were different according to gender. Young males said it was due to the little time that they spent with old people. However, young females reported that the main reason for this linguistic gap is the need to modernise vocabulary to overcome communication difficulties with people from different cultures.
6. Discussion
The present study sought to answer three research questions. To answer the first and second questions, a quantitative analysis of the collected data was conducted. The statistical analysis of the participants’ responses to the questionnaire showed that there was a statistically significant lexical gap between younger and older generations in the Jizani dialect. Thus, age can detect and cause lexical changes (Bordin, 2009; Nagy, 2011; Saladino, 1990; Sharma and Sankaran, 2011). The difference between the two generations was in favour of the new one. Most of the old participants’ answers were incorrect, indicating that the old people’s knowledge of new words was low. However, the young participants’ responses were approximately half correct and half incorrect, indicating that younger speakers have good knowledge of the old lexicons. The effect size of the gap was small since it was between only two generations (Nagy, 2011).
In addition, a statistically significant difference between young males and females was found. The statistical analysis revealed that young males outperformed their counterparts in their knowledge of the words used by the older generation. Although the effect size of this difference was small, it was still significant (Table 7). Hence, these statistics offer a clue as to how gender (Chambers and Schilling, 2018) relates to lexical changes over time.
The gap between the old and new generations can occur due to many reasons. Direct contact (Ahangari and Moradi, 2013) with other people around the world and the affordability of technology, which facilitates direct contact, has resulted in borrowed English words entering the Jizani dialect, such as [kjwt] “cute”, [jkansil] “to cancel” and [baːrrjstaː] “barista”. Interestingly, the word [mlaqliq] is a modified form of the word “lag (n)”, which can be traced back to English. It is used as an adjective. Furthermore, young speakers code-switch (Muttaqin et al., 2019) with English when they use certain words like [kjwt] “cute”. As mentioned earlier, the gap between the old generation and young females is greater than that between the older generation and younger males. The reason might be that women innovate lexical changes (Labov, 1990) by inserting new words or changing the meaning of existing ones. For instance, the word [xaqaq] “very beautiful” has been given another meaning by women.
A glance at Table 5 reveals that the old words [zahb] “fertile land”, [hwʃ] “animals” and [baːsil] “much” were salient among younger speakers in Jazan. However, [mxawwitʕ] “coming fast” and [dhʃwm] “jungle” were not known to the vast majority of the younger generation there. This indicates that words such as [mxawwitʕ] “coming fast” and [dhʃwm] “jungle” will not be known at all by the next generation.
The data collected from the participant interviews was analysed to uncover the reasons for this lexical gap. Old people spent an average of 0.83 h using social media. Therefore, old people scored low in their knowledge of new words. Young people reported that they spent about 5.16 h on social media. This may have increased their knowledge of new and borrowed words, which, in turn, increased the lexical gap between the two generations over time. Although old people said that they spent about eight hours every day with young people, their knowledge of the young generation’s words was insufficient. In contrast, young people’s knowledge of the old generation’s words was good, even though they spent only 2.16 h a day with old people. It can be assumed that older speakers explain unknown old words to their young children or grandchildren. Consequently, this raises young speakers’ knowledge of old terms.
Older speakers described technology-related words as the driving force for innovating new words and, thus, widening the lexical gap. The use of online games and social media gives young people access to people of other dialects, languages and cultures. This results in learning or borrowing words from other dialects and languages. On the other hand, younger speakers’ answers were divided according to gender. Young males said that they could hardly find time to sit and chat with old people for many reasons like school, friends, etc. The main reason, as per the young females’ point of view, was that they had to stay up to date with new words so they could overcome any cross-cultural communication difficulties.
From Table 7, it is obvious that young women spent more time than young men using social media. It was clear that young males performed better than young females on the questionnaire, even though they spent less time with the older generation than young females did. The reason for this is that women tend to use prestigious words (Gordon, 1997), while men tend to use words that show masculinity (Trudgill, 2000). In addition, men tend to use words used in their community, while women tend to use words used in cross-cultural communication (Hocini, 2011). Furthermore, interesting answers were elicited from female interviewees, such as “We need to keep up with the world” and “Our dialect is not understood, even by some of us”. This might indicate that women prefer using more prestigious words in their speech as Al-Qahtani (2015) and Al-Wer (1991) have concluded.
Like any other study, this research has some limitations. Firstly, many of the old people were illiterate and many did not use smartphones; consequently, they could not fill in the questionnaire without some help. Secondly, it was difficult to collect more responses from other participants because of the time constraint. Finally, the findings of this study cannot be generalised due to the small sample used in the questionnaire compared with the population, and the convenience sample used in the interviews.
7. Recommendations
This study offers important information about the lexical gap in the Jizani dialect between the old and new generations, and the reasons for this gap. Dialectologists and those who are interested in old lexicons can start detecting and registering endangered words before they vanish. Future studies can employ more social variables such as education and social class. I recommend that this study be replicated with the help of the English department at Jazan University to survey a large sample. This will make the results more accurate and generalisable.
8. Conclusion
This study attempted to find if the old words in the Jizani dialect are used by the younger generation and vice versa. It also sought to uncover the possible reasons for the differences in the words used by the two generations. The present study concluded that a lexical gap between the two generations does exist. The results revealed that time-consuming social media platforms and borrowing words from other languages and dialects, with the help of technology, are probable reasons for this gap. The tendency of females to use more prestigious words also plays a significant role in the difference. The findings were consistent with previous studies in the literature. The contribution this study might make is that dialectologists and sociolinguists might use the findings to understand how lexical change occurs in the Jazan community. In addition, the most endangered words could be registered before they completely vanish. It is recommended that this study be replicated using a richer questionnaire and a larger sample. There were some limitations in this study such as some of the old people not being able to read, write or use smartphones. In addition, the use of a small sample and the nonprobability sample made the findings ungeneralisable.
I would like to express my sincere gratitude to my supervisor who helped me finish this work.
Descriptions and characteristics of the sample
| Variable | Element | Frequency | Percentage |
|---|---|---|---|
| Gender | Male | 55 | 52.9 |
| Female | 49 | 47.1 | |
| Total | 104 | 100 | |
| Age | 50+ | 51 | 49 |
| 15–30 | 53 | 51 | |
| Total | 104 | 100 | |
Reliability statistics, (Cronbach’s alpha test values)
| Axis | N | N of items | Cronbach’s alpha |
|---|---|---|---|
| Old generation questionnaire | 51 | 10 | 0.856 |
| New generation questionnaire | 53 | 10 | 0.507 |
| Total | 104 | 20 | 0.741 |
Independent sample t-test of the difference between the old and new generations’ scores
| Variable | Element | Mean | T | p-value |
|---|---|---|---|---|
| Generation | Old generation | 3.588 | −3.221 | 0.002 |
| New generation | 5.208 |
Descriptive statistics of new words (for old generation)
| Element | Answer | Freq | (%) | Meaning |
|---|---|---|---|---|
| What does [xaqaq] mean | correct | 15 | 29.4 | Very beautiful (adj) |
| incorrect | 36 | 70.6 | ||
| Total | 51 | 100 | ||
| What does [jswqhaː] mean | correct | 22 | 43.1 | To fool (v) |
| incorrect | 29 | 56.9 | ||
| Total | 51 | 100 | ||
| What does [baːrrjjstaː] mean | correct | 17 | 33.3 | Barista (n) |
| incorrect | 34 | 66.7 | ||
| Total | 51 | 100 | ||
| What does [jkansil] mean | correct | 30 | 58.8 | To cancel (v) |
| incorrect | 21 | 41.2 | ||
| Total | 51 | 100 | ||
| What does [muzzah] mean | correct | 23 | 45.1 | Very beautiful (adj) |
| incorrect | 28 | 54.9 | ||
| Total | 51 | 100 | ||
| What does [kjwt] mean | correct | 14 | 27.5 | Cute (adj) |
| incorrect | 37 | 72.5 | ||
| Total | 51 | 100 | ||
| What does [mlaqliq] mean | correct | 3 | 5.9 | Lagging (adj) |
| incorrect | 48 | 94.1 | ||
| Total | 51 | 100 | ||
| What does [darbaːwj] mean | correct | 23 | 45.1 | Type of youngers (n) |
| incorrect | 28 | 54.9 | ||
| Total | 51 | 100 | ||
| What does [jsallik] mean | correct | 24 | 47.1 | To flatter (v) |
| incorrect | 27 | 52.9 | ||
| Total | 51 | 100 | ||
| What does [jflim] mean | correct | 12 | 23.5 | Do stunts (v) |
| incorrect | 39 | 76.5 | ||
| Total | 51 | 100 | ||
Descriptive statistics of old words (for new generation)
| Element | Answer | Freq | (%) | Meaning |
|---|---|---|---|---|
| What does [baːsil] mean | correct | 47 | 88.7 | Much (adj) |
| incorrect | 6 | 11.3 | ||
| Total | 53 | 100 | ||
| What does [lanʤ] mean | correct | 33 | 62.3 | New (adj) |
| incorrect | 20 | 37.7 | ||
| Total | 53 | 100 | ||
| What does [jahtub] mean | correct | 23 | 43.4 | To walk fast (v) |
| incorrect | 30 | 56.6 | ||
| Total | 53 | 100 | ||
| What does [dhʃwm] mean | correct | 11 | 20.8 | Jungle (n) |
| incorrect | 42 | 79.2 | ||
| Total | 53 | 100 | ||
| What does [jxawwil] mean | correct | 23 | 43.4 | To look at something far (v) |
| incorrect | 30 | 56.6 | ||
| Total | 53 | 100 | ||
| What does [kassaːr] mean | correct | 18 | 34 | Shopkeeper (n) |
| incorrect | 35 | 66 | ||
| Total | 53 | 100 | ||
| What does [zahb] mean | correct | 39 | 73.6 | Fertile land (n) |
| incorrect | 14 | 26.4 | ||
| Total | 53 | 100 | ||
| What does [hwʃ] mean | correct | 45 | 84.9 | Animals (n) |
| incorrect | 8 | 15.1 | ||
| Total | 53 | 100 | ||
| What does [masʕbaʕ] mean | correct | 23 | 43.4 | Funnel (n) |
| incorrect | 30 | 56.6 | ||
| Total | 53 | 100 | ||
| What does [mxawwitʕ] mean | correct | 14 | 26.4 | Coming fast (adj) |
| incorrect | 39 | 73.6 | ||
| Total | 53 | 100 | ||
Independent sample t-test of the difference between young males’ and females’ scores
| Variable | Element | Mean | T | p-value |
|---|---|---|---|---|
| Gender | Male | 6.045 | 2.846 | 0.006 |
| Female | 4.613 |
The average time young males and females spent with old people and on social media
| Variable | Element | N | Avg. on social media | Avg. with old people |
|---|---|---|---|---|
| Gender | Male | 3 | 4.33 h | 1.3 h |
| Female | 3 | 6 h | 3 h | |
| Total average | 6 | 5.16 h | 2.16 h | |
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