The Journey of a Word: An Action Research Intervention of Morphemic Analysis and Etymology for a Middle School Gifted and Talented Class

Sixth-grade students who had been identified as gifted and talented participated in a literacy intervention designed and implemented by the first author as part of an action research project. These students were meeting the grade-level standards in literacy, so the project aimed to push their vocabulary knowledge further in order to prepare them for the complex vocabulary they encounter in their independent reading and assigned content units. This daily intervention directly taught students the origins and histories of words and word parts from Latin, Greek, Germanic, and French languages, introduced morphemic analysis strategies, and gave them techniques to analyze the words’ meanings based on that information. Content-specific vocabulary, as well as general vocabulary knowledge of the participating students increased significantly. Throughout the intervention, students’ confidence in vocabulary knowledge improved, and they gained a deeper understanding of the nuances of language as their ability to apply this knowledge in other contexts grew and facilitated better understanding of the words they read.

Replacing Out-of-Vocabulary Words with an Appropriate Synonym Based on Word2VnCR

The most typical problem in an analysis of natural language is finding synonyms of out-of-vocabulary (OOV) words. When someone tries to understand a sentence containing an OOV word, the person determines the most appropriate meaning of a replacement word using the meanings of co-occurrence words under the same context based on the conceptual system learned. In this study, a word-to-vector and conceptual relationship (Word2VnCR) algorithm is proposed that replaces an OOV word leading to an erroneous morphemic analysis with an appropriate synonym. TheWord2VnCR algorithm is an improvement over the conventional Word2Vec algorithm, which has a problem in suggesting a replacement word by not determining the similarity of the word. After word-embedding learning is conducted using the learning dataset, the replacement word candidates of the OOV word are extracted. The semantic similarities of the extracted replacement word candidates are measured with the surrounding neighboring words of the OOV word, and a replacement word having the highest similarity value is selected as a replacement. To evaluate the performance of the proposed Word2VnCR algorithm, a comparative experiment was conducted using the Word2VnCR and Word2Vec algorithms. As the experimental results indicate, the proposed algorithm shows a higher accuracy than the Word2Vec algorithm.

Enhancing Technical Vocabulary Through Morphological Analysis Instruction For Biology-majored Students

This paper aims to investigate the effectiveness of morphological analysis instruction on gradetenbiology-major studentsin TanTaoHigh SchoolfortheGifted inLong An, Vietnam, andto find out whether they can catch up with the level of biotechnology students in Tan Tao University, in terms of science vocabulary performance. The instruction selectively targeted technical multisyllabic words that occur frequently in the participants’ corpus. Thirty-one students including eighteen grade-ten biology students as the experimental group and thirteen biotechnology students as the control group participated in the study. For data collection, pre-posttest was designed, validated and applied for the experimental and control group. Apart from the regular teaching method, the experimental group also received explicit morphemic analysis instruction, while the control group only received their regular teaching. Pretest to posttest results revealed that each group registered an increase in the respective means, however, the experimental group surpassed the control group up to 5.9 mean difference. Morphemic analysis confirms its effectiveness in boosting the students’ vocabulary acquisition of multisyllabic terminologies that facilitates their learning. The paper ended with some pedagogical implications for teaching technical terms.

TO THE QUESTION ABOUT MORPHEMIC STRUCTURE OF PERSONAL PRONOUNS OF THE AVAR LANGUAGE

The morphemic analysis of the five personal pronouns of the Avar language presented in the article revealed the following. 1. Having the same base structures, singular and plural personal pronouns have different struc-tures of root morphemes. The root morphemes of the singular personal pronouns are represented by two-component consonant + vowel structures. The root morphemes of plural personal pronouns are represented by three-component consonant + vowel + consonant structures. 2. All case forms of the singular personal pro-nouns are formed from an indirect basis. All case forms of personal plural are formed from a direct basis.

One more time about the relation between morphemic analysis and word-formation analysis

One of the basic criteria when it comes to describing the surface structure of the derivative lexical units is distinguishing morphemic and word-formation analysis. Distinguishing the two types of analysis on the grounds of divisibility and derivation principles in practice makes it possible to avoid mixing up the monoverbal lexical derivatives with non-derivative ones, yet the morphemically divisible units (words) especially when we have formal equality of the individual structural elements. We could distinguish morphemic and word-formation analysis thanks to the usage of approach from form to meaning in order to define the exact number of the wordforming formants in each and every language, including Bulgarian. This is essential to the lexicographic practice when it comes to elaborating various types of wordforming vocabularies, in order to achieve precision and scientific objectiveness in interpreting and presenting the language facts and phenomena.