Multilingual Education and Interference: Written Ungrammatical Tag-switching Among Pre-service Teachers of English Language

This research aims to: (1) show the ungrammaticality of pre-service teachers\u27 (Bachelor III students\u27) written tag-switching models and this is disapproving since these subjects are English teachers-to-be. (2) It also tracks tokens of interference of Kirundi, French, Kiswahili and English languages in the Bachelor III students\u27 written tag-switching examples as a result of the Burundian multilingual education system.The study refers to the observation and Testing as suggested respectively by Cohen et al. (2006) and Hughes (2003). The researcher\u27s unstructured observation participated in his review of observational data before suggesting any explanation for the phenomena being observed. The test given helped measure on the one hand those pre-service teachers\u27 achievements of the course objectives and diagnose their strengths and weaknesses on the other hand. The subjects of the study consisted of thirty-six (36) students whose preference was tag-switching in an Exam of Sociolinguistics with the question framed as follows: “Among the different code switching types, choose one and exemplify it with three examples.” The Kuder- Richardson formula 20 (KR-20) and Standard Error Measure (SEM), provided helpful information when having to take decisions about individuals on the basis of their performance in a test such as the one given during this research, (Hughes, ibid:224). The research findings reveal a mismatching between the subjects\u27 level of study and the written tag-switching examples that they gave: after correction done diligently and skilfully, ungrammaticality is a case and it includes the subjects\u27 wrong tense use at the tag level and the occurrence of wrong choice of tenses, aspects and mood (either in Kirundi, French and Kiswahili) in the part before tag level. The cause of these erroneous tag- switching examples is revealed to take source in the multilingual education system operational in Burundi. Keywords: Educational multilingualism, interference, tag-switching and ungrammaticalit

Discrepancies in meeting OREO guidelines: The Teacher-researcher’s sacrifice and new skill set needs

In this evaluation research, the researcher aimed at examining the extent to which Hebei Foreign Studies University (hereafter referred to HFSU) implementated of the O.R.E.O guidelines during COVID-19 lockdown. To collect data, the researcher used the document analysis, an interrater checklist, and participant observation. As the study used both the qualitative and quantitative data, the analysis was equally qualitative and descriptive statistics was used to analyse quantitative data. The major findings were that HFSU did well as two raters found out that fourteen criteria out of sixteen on the rating metrics were fulfilled. The level of O.R.E.O implementation of that university during the Covid-19 lockdown (Semester I, academic year 2020-2021) is “Very Highly” (92%) but it could have done more than that by adjusting few things like insuring undisturbed learning space by parents or guardians and cross-checking information reported both by students and teachers concerning the daily activities of the online teaching-learning

Discrepancies in assessing undergraduates’ pragmatics learning

The purpose of this research was to reveal the level of implementation of authentic assessment in the pragmatics course at the English Education Department of a university. Discrepancy Evaluation Model (DEM) was used. The instruments were questionnaire, documentation, and observation. The result of the research shows that respectively, the effectiveness of definition, installation, process, and production stages in logits are -0.06, -0.14, 0.45, and 0.02 on its aspect of the assessment methods’ effectiveness in uncovering students’ ability. Such values indicate that the level of implementation fell respectively into ‘very high’,’high’, ‘low’, and ‘very low’ categories.  The students’ success rate is in ‘very high’ category with the average score of 3.22. However, the overall implementation of the authentic assessment fell into a ‘low’ category with the average score of 0.06. Discrepancies leading to such a low implementation are the unavailability of the assessment scheme, that of scoring rubric, minimal (only 54.54%) diversification of assessment methods, infrequency of the lecturer’s feedback on the students’ academic achievement, and the non-use of portfolio assessment

Evaluating the Implementation of Authentic Assessment in the Pragmatics Course at the English Education Department, Yogyakarta State University

This research aims at revealing the extent to which is the implementation of authentic assessment in the pragmatics course at the English Education Department, Yogyakarta State University. The model used in this program evaluation is the Discrepancy Evaluation Model (DEM). It was carried out at the English Education Department, English Language and Literature Study Program and three data collection techniques were used, including questionnaire, documentation, and observation. Part of the data collected using the questionnaire were analysed using the quantitative analysis technique, while the data obtained through documentation, observation, and some data collected using the questionnaire were analysed using the qualitative analysis. The results of the study show that the implementation of authentic assessment in the pragmatics course at the program definition stage falls into the “High” category with -0.06 of Item Measure Order average. The program installation stage is in the “High” category with the average equal to -0.14, and the program process stage is also in the “Low” category with 0.45 of Item Measure Order average score. Concerning the program product stage, its Item Measure Order average is 0.02 for its aspect of the assessment methods’ effectiveness in uncovering students’ ability, skills, and competence. It is consequently ranked in the “Low” category. The other aspect of the program product stage is the students’ final scores in the pragmatics course and its average is 3.22, which indicates that the students’ success rate is in the “Very High” category. However, the average score for the implementation of the authentic assessment in the pragmatics course is 0.06, which indicates it is ranked in the “Low” category. Such a low implementation is due to the unavailability of the assessment scheme and scoring rubric and a minimal (only 54.54%) diversification of assessment methods. On the top of that, there is infrequency of the lecturer’s feedback on the students’ academic achievement and no portfolio assessment was used, which means the students’ learning is not monitored in a comprehensive manner as indicated in the curriculum

Prediction model of teacher candidate student graduation status: Decision Tree C4.5, Naive Bayes, and k-NN

This study aims to determine the prediction model of the graduation status of prospective teacher students at IAIN Bone in terms of attributes, accuracy levels, and differences in the level of accuracy produced in the attributes of decision tree C4.5, Naïve Bayes, and k-NN data mining algorithms. This research uses a quantitative approach by adopting the Data Mining method. This research was conducted at IAIN Bone. The data collection process in this study used documentation techniques in the form of data on alumni of the Tarbiyah Faculty of IAIN Bone. The data analysis used was a descriptive analysis using decision tree C4.5, Naive Bayes, and k-NN data mining algorithms assisted by the RapidMiner application.  The results of this study show that (1) model prediction of the graduation status of prospective teacher students in IAIN Bone in terms of attributes generated in the Decision Tree C4.5 and Naïve Bayes data mining algorithms  consist of gender, age, Semester 1 IP, Semester 2 IP, Semester 3 IP, Semester 4 IP, and GPA, while the attributes produced in   k-NN data mining algorithm  consists of gender, regional origin, number of siblings, age, IP Semester 1, IP Semester 2, IP Semester 3, IP Semester 4, and GPA; (2) model prediction of graduation status of iain bone teacher candidate students in terms of the accuracy rate generated in the Decision Tree C4.5 data mining algorithm  of 93.90%, Naïve Bayes by 90.24%, and k-NN of 92.07%; and (3) there was no significant difference between the accuracy rate produced by decision tree's data mining algorithm.  C4.5 and Naïve Bayes (p-value = 1.00); Decision Tree C4.5 and k-NN (p-value = 1.00); as well as Naïve Bayes and k-NN (p-value = 1.00) in predicting the graduation status of iain bone teacher candidate students