By Rushan Ziatdinov
The knowledge of languages is a competitive advantage for humans because it can be extremely beneficial for one's future and career. Language acquisition has been proven to increase a learner's cognitive function, which includes ― but is not limited to ― improved problem-solving abilities and memory function.
Vocabulary learning is crucial to language acquisition, according to Jeanette Decarrico (2001), whether the language is a first, second or foreign language. After people have learned vocabulary in their first language (L1), also known as the "native language" or "mother tongue," the process of acquiring vocabulary in the second language (L2), referred to as second language vocabulary acquisition, occurs.
Although vocabulary has not always been prioritized in language instruction, interest in its role in L2 learning has expanded rapidly in recent years, and experts stress the importance of both the instructor and the learner adopting a systematic and principled approach to acquiring vocabulary.
By examining the frequency of words and phrases present in a document, modern technologies such as high-level programming languages enable the creation of a specialized vocabulary. A "frequency dictionary" is exactly what the name suggests: a list of a language's most commonly used words.
Advances in technology, which were unavailable to previous academics, have substantially aided the development of the actual lists for frequency dictionaries. A modern frequency dictionary represents a significant resource not just because of the information it offers, but also because it emphasizes the importance of words and phrases.
Frequency dictionaries can be created based on a particular e-book or its chapters, a PDF document, or a presentation. The variety of formats makes such dictionaries attractive for classes with complex vocabulary, such as in engineering or the social sciences. Professors and teachers can develop a frequency dictionary for every lecture or class, which will undoubtedly increase the active participation of learners by allowing them to translate the prepared terminology into their mother tongues. Learners can also add some useful examples of sentences, which will help them to understand a word or phrase.
Alternatively, given that instructors are usually busy preparing lecture materials, all these vocabulary-related tasks can be given to learners as weekly homework assignments. Instructors' presentations can be shared via a learning management system in advance, and learners can then develop a frequency dictionary for forthcoming lectures.
Before attending a class, learners can study or even memorize the most popular words and phrases and their meanings, allowing them to better understand what the instructor discusses during the lecture. At the beginning of each lecture, the instructor can also define the meanings of some important frequently used words and phrases from the current lecture. These words and phrases can also be sorted alphabetically and shared with learners in printed form.
Frequency dictionaries can be developed using the Python programming language, in which two lists can be created from the given text: one for words and the other for the frequencies of the words and phrases. Alternatively, those who do not know how to program can use free online services such as Word Counter (https://countwordsfree.com/), Count Word Frequency (https://www.browserling.com/tools/word-frequency), or others.
For example, Word Counter allows the user to extract the 1,000 most popular words from a text and calculate phrase density. Moreover, excluding stop words from the list and varying the number of symbols in a word are also possible in this online service.
Another proprietary kind of software called WordStat (https://provalisresearch.com/) is available for content analysis and text mining, and can be used for free during a trial period. Specific approaches can provide descriptive data such as word frequencies and document lengths in 46 languages. WordStat accepts documents in txt, rtf, html, pdf, and other formats and can be run in either explore mode (extracting frequent words, phrases, and topic) or expert mode (with dictionaries, crosstab, cooccurence, etc.).
The WordStat software has recently been included in Ziatdinov's list of free legal software (https://www.ziatdinov-lab.com/student-support/free-software), which has been accessed thousands of times during the COVID-19 pandemic and included in the list of Remote Teaching Resources for Business Continuity, one of the main lists of teaching resources for U.S. professors during the pandemic.
After the extraction of the most popular words and phrases is completed, an instructor can create a table in an online Google Spreadsheet file and share a hyperlink with learners so that anyone with the link can edit the document. Learners can work collaboratively and translate the terminology into their mother tongues, find and add synonyms, and provide useful examples in the form of sentences.
They can also compare the translations in Google Spreadsheet by using a column with the formula, =GOOGLETRANSLATE (cell with text, "source language", "target language"), can be used for an automated translation. Finally, the number of translated words and phrases can be computed for every learner by using the COUNTIF function, and grades can be assigned to every learner. In addition, if necessary, instructors can integrate language terminology-related questions into exams, which will help to enrich learners' vocabulary.
Studying a frequency dictionary for each forthcoming lecture will lead to a better understanding of the lecture content and improve learners' language skills. For this reason, the development of such specialized dictionaries should be supported by educational organizations. Schools, colleges, universities, and the Ministry of Education should pay particular attention to classes taught in foreign languages and support them as much as possible to increase the attractiveness, competitiveness and prestige of the national educational system.
Rushan Ziatdinov (ziatdinov.rushan@gmail.com) is a professor in the Department of Industrial Engineering at Keimyung University, Daegu.
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Vocabulary learning is crucial to language acquisition, according to Jeanette Decarrico (2001), whether the language is a first, second or foreign language. After people have learned vocabulary in their first language (L1), also known as the "native language" or "mother tongue," the process of acquiring vocabulary in the second language (L2), referred to as second language vocabulary acquisition, occurs.
Although vocabulary has not always been prioritized in language instruction, interest in its role in L2 learning has expanded rapidly in recent years, and experts stress the importance of both the instructor and the learner adopting a systematic and principled approach to acquiring vocabulary.
By examining the frequency of words and phrases present in a document, modern technologies such as high-level programming languages enable the creation of a specialized vocabulary. A "frequency dictionary" is exactly what the name suggests: a list of a language's most commonly used words.
Advances in technology, which were unavailable to previous academics, have substantially aided the development of the actual lists for frequency dictionaries. A modern frequency dictionary represents a significant resource not just because of the information it offers, but also because it emphasizes the importance of words and phrases.
Frequency dictionaries can be created based on a particular e-book or its chapters, a PDF document, or a presentation. The variety of formats makes such dictionaries attractive for classes with complex vocabulary, such as in engineering or the social sciences. Professors and teachers can develop a frequency dictionary for every lecture or class, which will undoubtedly increase the active participation of learners by allowing them to translate the prepared terminology into their mother tongues. Learners can also add some useful examples of sentences, which will help them to understand a word or phrase.
Alternatively, given that instructors are usually busy preparing lecture materials, all these vocabulary-related tasks can be given to learners as weekly homework assignments. Instructors' presentations can be shared via a learning management system in advance, and learners can then develop a frequency dictionary for forthcoming lectures.
Before attending a class, learners can study or even memorize the most popular words and phrases and their meanings, allowing them to better understand what the instructor discusses during the lecture. At the beginning of each lecture, the instructor can also define the meanings of some important frequently used words and phrases from the current lecture. These words and phrases can also be sorted alphabetically and shared with learners in printed form.
Frequency dictionaries can be developed using the Python programming language, in which two lists can be created from the given text: one for words and the other for the frequencies of the words and phrases. Alternatively, those who do not know how to program can use free online services such as Word Counter (https://countwordsfree.com/), Count Word Frequency (https://www.browserling.com/tools/word-frequency), or others.
For example, Word Counter allows the user to extract the 1,000 most popular words from a text and calculate phrase density. Moreover, excluding stop words from the list and varying the number of symbols in a word are also possible in this online service.
Another proprietary kind of software called WordStat (https://provalisresearch.com/) is available for content analysis and text mining, and can be used for free during a trial period. Specific approaches can provide descriptive data such as word frequencies and document lengths in 46 languages. WordStat accepts documents in txt, rtf, html, pdf, and other formats and can be run in either explore mode (extracting frequent words, phrases, and topic) or expert mode (with dictionaries, crosstab, cooccurence, etc.).
The WordStat software has recently been included in Ziatdinov's list of free legal software (https://www.ziatdinov-lab.com/student-support/free-software), which has been accessed thousands of times during the COVID-19 pandemic and included in the list of Remote Teaching Resources for Business Continuity, one of the main lists of teaching resources for U.S. professors during the pandemic.
After the extraction of the most popular words and phrases is completed, an instructor can create a table in an online Google Spreadsheet file and share a hyperlink with learners so that anyone with the link can edit the document. Learners can work collaboratively and translate the terminology into their mother tongues, find and add synonyms, and provide useful examples in the form of sentences.
They can also compare the translations in Google Spreadsheet by using a column with the formula, =GOOGLETRANSLATE (cell with text, "source language", "target language"), can be used for an automated translation. Finally, the number of translated words and phrases can be computed for every learner by using the COUNTIF function, and grades can be assigned to every learner. In addition, if necessary, instructors can integrate language terminology-related questions into exams, which will help to enrich learners' vocabulary.
Studying a frequency dictionary for each forthcoming lecture will lead to a better understanding of the lecture content and improve learners' language skills. For this reason, the development of such specialized dictionaries should be supported by educational organizations. Schools, colleges, universities, and the Ministry of Education should pay particular attention to classes taught in foreign languages and support them as much as possible to increase the attractiveness, competitiveness and prestige of the national educational system.
Rushan Ziatdinov (ziatdinov.rushan@gmail.com) is a professor in the Department of Industrial Engineering at Keimyung University, Daegu.
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