Table 1: Students’ report on skill/strategy transfer abilities in English and Arabic In terms of the use of background knowledge in English, students reported that the 1ad problems reflecting on what they had read. H ranslate into Arabic with an aim of understandin 0 code-switching when required and could adj aimed to use their background knowledge when g En ust vith the use of background knowledge in A rabic, ead, used background knowledge when they read an owever, they reported an adequate ability t glish content better. They also resorte their reading speed. The students als reading and writing in English. Furthermor the students could reflect upon what they he d write, and adjusted their speed whe eading difficult content. However, they often resorted to code-switching when they expresse hemselves (See Table 2). Table 4: English and Arabic teachers’ report on the use of background knowledge difficult text. Students also did not refer to dictionaries when required and resorted to code- vocabulary to understand new words. Table 1 demonstrates the gender of participants. It is seen that 87 females (93.5%) and wanlac (4. ROL.) Kank asnntad in FAA ohics Table 2: Frequency of GT use Table3: Descriptive analysis of the use of GT Table 4: Descriptive analysis of PU often use this GT.7% seldom use it, and 5.45% never use GT for academic purposes. SA=Strongly Agree, A=Agree, N=Neutral, DA=Disagree, SDA=Strongly Disagree Table 5: Descriptive analysis of PEOU easiness and fastness of GT for doing assignment and language learning; however, 38% held Figure 6: The percentage of agreement of Accuracy of GT Table 1: Distribution of the Respondents two different texts that had the same length (1,100 words). Each reading was timed and tape- 3.2.2. Reading Texts Figure 1: Levels of Respondents’ Reading Prosody Figure 2: Levels of Respondents’ Reading Prosody by Gender poor reading prosody. average level while another 71 that comprised 23 (10.9%) males and 48 (22.9%) females had An investigation on several prosodic features namely reading expression and reading Figure 4: Levels of Respondents’ Reading Expression and Reading Volume Figure 5: Levels of Respondents’ Reading Expression and Reading Volume by Gender Figure 6: Levels of Respondents’ Reading Expression and Reading Volume by Academic Semester 1 respondent (Semester 1 student) had good reading expression and volume. 3 read naturally with occasional expression in certain parts of the assigned reading text. Only Figure 7: Levels of Respondents’ Phrasing in Reading Figure 8: Levels of Respondents’ Phrasing in Reading by Gender possessed well-phrased reading manner. Figure 9: Levels of Respondents’ Phrasing in Reading by Academic Semester respondents - 1 Semester 1 and 1 Semester 3 respondents - demonstrated well-phrased reading. remaining 2 males and 1 female possessed good reading smoothness. satisfactory reading smoothness while 31 (14.7%) Semester 1 and 46 (22%) Semester ‘ semester 1 and 2 (1%) Semester 3 respondents had well- phrased reading smoothness. respondents had reasonably well reading smoothness. It was also found that only 1 (0.5%) Semester 1 and 2 (1%) Semester 3 respondents had well-phrased reading smoothness. In terms of reading smoothness, Semester 3 respondents demonstrated a greater mean respondents had reasonably well reading smoothness. It was also found that only 1 (0.5%) Figure 13: Levels of Respondents’ Reading Pace Figure 14: Levels of Respondents’ Reading Pace by Gender speed. No respondents had good reading pace. Figure 16: Levels of Respondents’ Reading Comprehension Abilities respondents (2 males and 10 females) had very poor reading comprehension. Majority of th The analysis on the respondents’ reading comprehension abilities according to Table 2: Correlation Score between Reading Prosody and Reading Comprehension 5. Discussion Figure 18: Levels of Respondents’ Reading Comprehension Abilities by Academic Semester Table 3: Native speaker demographics The materials comprise the essays written by TESOL student teachers in their The materials comprise the essays written by TESOL student teachers in their cademic writing course. The rubric and native speakers were also employed to assess the aturalness of collocations. instructions were provided for the raters. The following table illustrates the native speakers enhancing teaching and learning, which are presented chronologically. satisfaction, and student habitual significantly affect continued use, while students’ satisfaction Venkatesh et al. (2003) have empirically put forth an IS theory known as Unified Theory of Acceptance and Use of Technology (UTAUT). UTAUT possesses four direct letermining factors: performance expectancy, social influence, effort expectancy, and acilitating conditions. It also has behavioral intention and uses behavior as a dependent variable. UTAUT theory also has four moderators: age, gender, the voluntariness of use and *xperience, and moderating relationships between dependent and independent variables. The letails of the UTA UT theory are demonstrated in Figure 2. details of the UTA UT theory are demonstrated in Figure 2. experience, and moderating relationships between dependent and independent variables. The Figure 3: The proposed conceptual model for Educational game learning based on Table 12: Faculty As indicated in Table 12, in total, 163 students participated in the current study who were from the Faculty Of Management (83, 50.9%), Faculty Of Creative Art& Human Development (72, 44.2%), and Center For Profesional & General Studies (8,4.9%). It is seen Table 14: Gender CaMpuses. As illustrated in Table 13, 163 students took part in the study who live on-campus/hostel belongs to attitude (ATT), while SP has the least mean score. Table 16: Descriptive Statistics Table 18: Variables Entered/Removed Table 19: Model Summary As indicated in Table 19, the R square is .391. It means that the independent variables in the model account for 39% of changes in the dependent variable. the subcategories associated with each different learning style. students’ learning styles and approaches to study may significantly bear on their academic to the needs of the students and help with the betterment of their English language capabilities. Table 1. Read/ Write Learners’ Scores presented in the table and figures below: Table 2. Visual Learners’ Scores Table 3. Aural Learners’ Scores Table 4. Kinesthetic Learners’ Scores Table 5. Average English score of different learning styles As can be seen from Table 5, the learners who preferred the Read/W nite learning style the highest average scores and which learning styles produced the lowest average scores. Figure 7. Kinesthetic Learners’ Scores Table 2: Reliability Statistics “olQMiCdlt QULCLENCe, PS U.U0 Case A: Attention, Relevance, Confidence, and Satisfaction between Online and F2F learning comparison Table 3: Means for 4-dimensions in Motivation values for each dimension in motivation, mean for overall motivation, and dependent samples According to Table 3, the mean for Attention in F2F learning (3.65) was higher than the mean in online learning (2.98); in addition, there is a significant difference in the mean for 4.3 Analysis on Each Dimension in Motivation A total of 31 items is divided into four subsets according to Attention (8 items), Relevance (7 items), Confidence (8 items), and Satisfaction (8 items). There were 11 reverse low motivation levels in online learning compared to only 7% in F2F learning. Table 6: Individual Item in Each Dimension comparison
