Personal experience of using XIPUAI to enhance teaching and learning
Abstract
Since the introduction of XIPUAI at XJTLU, I have been intrigued by its capabilities. After several trials, I found this tool can significantly reduce the time of material design when prompted effectively. In addition, it can also become an effective tool for enhancing students’ self-regulated learning by generating desirable sources to meet their personalized needs.
 
 
Introduction
 
During the first semester of the academic year 2023-2024, I underwent an enlightening training session on utilizing XIPUAI provided by EDU. Additionally, a lecture by guest speaker Dr. Kou further motivated me to start exploring the application of this tool. Based on my own experience, I believe this tool can not only reduce lesson preparation time for educators but also increase students’ learning autonomy. In this article, I will describe two personal applications of XIPUAI and discuss the advantages and disadvantages of my practice.
 
 
Using XIPUAI to generate vocabulary quiz
 
Accumulating enough vocabulary is vital in the process of language acquisition as vocabulary is the foundation of four language skills (Groot, 2000; Schmitt 2000). Figure 1, illustrating Ebbinghaus’ forgetting curve (Zhu, 2020, p.901), reveals the swift decay of newly acquired knowledge, emphasizing that learners may rapidly forget information after the first day, with only about 10% retention after a week without timely review. Therefore, the importance of timely reviewing vocabulary cannot be ignored. Furthermore, scholars such as Laufer (1998) and Webb (2007) have emphasized the crucial role of repetition in vocabulary learning. Based on those, I usually help students review the words and phrased in the next day and again within the following week, hoping the retention of new vocabulary can achieve a relatively high level. Apart from the frequency of review, the method is also worth considering. According to Pica (1997), traditional dictation may have low efficiency, so I always require students to choose the correct word or phrase to complete a sentence, which provides a co-text for learners. Co-text, defined as the words and phrases surrounding a lexical item (Lewis, 1997), ensures a more holistic understanding of vocabulary within its contextual setting.
 
 
Figure 1: Ebbinghaus forgetting curve (Zhu, 2020, P901)
 
 
However, it is usually time-consuming to design a desirable quiz to review the newly learned lexical items. Previously, my approach involved using an e-dictionary to choose suitable sentences, followed by the laborious task of devising two or more additional options. Fortunately, with the help of XIPUAI, I can create a vocabulary quiz very quickly if I can give clear instructions. Figure 2 is one example of my prompt and the quiz generated by XIPUAI.
 
 
Figure 2: a quiz generated by XIPUAI
 
 
The advantages of using XIPUAI to generate a vocabulary quiz are quite obvious. Notably, it affords me substantial time savings, as creating a new quiz becomes a swift task by simply modifying the words and phrases to be tested in the prompt.  Within 10 seconds, a desirable quiz is presented, which significantly reduces my preparation time.
 
 
However, as a user of XIPUAI, I should emphasize the importance of providing clear instructions to optimize the tool’s outcomes. I have encountered various undesirable results in my initial experiences. For example, in the provided prompt, you’ll notice my use of two sentences to precisely outline my expectations for the two additional options in each question. This precaution stems from the observation that XIPUAI might include all options from the list of words and phrases to be tested. By specifying that the extra options should not be from my list, I received a new quiz. However, I observed that the alternatives provided were synonyms of the tested words or phrases, potentially causing confusion for students. Subsequently, I refined my instructions further, resulting in a more satisfactory quiz. Therefore, for those new to XIPUAI, I strongly recommend exercising caution in interpreting the tool’s responses and adjusting prompts accordingly to attain optimal results.
 
 
Instructing students to use XIPUAI to prepare for speaking test 
 
For year 1 students here in China, the transition from high school to university often brings about significant differences in their academic experiences. In high school, they are pressured by constant quizzes and exams, strictly following the teacher-prescribed study plans, which leads to limited experience of autonomous learning. Conversely, in university, the frequency of exams is much lower, placing greater responsibility on students to independently prepare for assessments. Thus, learning autonomy becomes very important for year 1 students.
 
 
In my classes, year 1 students usually feel very worried about the speaking assessment. The reason may be that in most provinces in China, speaking is not assessed in National College Entrance Examination, and accordingly their speaking ability is largely ignored by teachers. Nevertheless, at XJTLU, speaking holds significant weight in the English for Academic Purposes (EAP) course. Despite this, there is limited class time dedicated to practicing speaking skills. Recognizing the need for students to alleviate anxiety through autonomous practice, I introduced the use of XIPUAI as a valuable tool for preparing for the speaking assessment. One part of the speaking test in semester 1 of our module is answering questions related to the 10 topics in our textbook. Students always asked for the question bank used in last year, which is not useful since our textbook has been changed.
 
 
Instead, XIPUAI can be a good tool for them to prepare for speaking assessment. In figure 3, an illustrative example demonstrates how XIPUAI can assist students in preparing for the speaking assessment. XIPUAI can generate some questions as well as lexical items related to a certain topic. When students perceive a direct connection between their activities and the impending assessment, their motivation usually will be high (Nicol & MacFarlane-Dick, 2006). Introducing this method to prepare for the speaking test garnered an overwhelmingly positive response from students. During an in-class trial, they found the approach to be straightforward and effective, eliminating the need for outdated question banks associated with previous textbook editions. Since implementing this approach, no more students came to me asking for question bank used in previous years. It is apparent that students have embraced the autonomy provided by XIPUAI, using the tool to independently and confidently prepare for their assessments.
 
 
Figure 3: an example of using XIPUAI to help students prepare for speaking test
 
 
This practice with XIPUAI yields two significant benefits. As mentioned earlier, the first one involves fostering students' autonomous learning, while the second lies in the potential for students to achieve more academically. It has been mentioned by some scholars that effective utilization of technologies may lead to a learner’s better achievement (Schwartz, 2014; Wong et al, 2021). Since XIPUAI is an easily accessible tool for XJTLU students, it serves as a readily available tool to address academic challenges at any time and place, contributing to their overall personal development.
 
 
However, one major limitation persists in this practice. While XIPUAI enables students to receive questions for preparation, it falls short in providing feedback on their oral responses. Though students can engage in speaking practice with peers, my personal experience indicates that low-level students may struggle to offer constructive suggestions to one another. Simultaneously, it is impractical for every student to practice with a teacher. Therefore, if XIPUAI were to offer feedback services for students' speaking performances, it could significantly enhance their ability to autonomously prepare for speaking tests.
 
 
Conclusion
 
In this article, I have introduced how XIPUAI can be a valuable asset for both teachers in designing instructional materials and students in autonomously preparing for assessments. I firmly believe that with more careful trials of using this tool, both teachers and students can benefit greatly.
 
 
 
References:
 
Groot, P. J. M. (2000). Computer Assisted Second Language Vocabulary Acquisition. Language Learning & Technology: A Refereed Journal for Second and Foreign Language Educators, 4(1), 60–81. https://doi.org/10.1111/0023-8333.00110
 
Laufer, B. (1998). The Development of Passive and Active Vocabulary in a Second Language: Same or Different? Applied Linguistics, 19(2), 255–271. https://doi.org/10.1093/applin/19.2.255
 
Lewis, M. (1997). Implementing the lexical approach: putting theory into practice. Language Teaching Publications.
 
Nicol, D. & MacFarlane-Dick, D. (2006). Formative assessment and self-regulated learning: a model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218.
 
Pica, T. (1997). Tradition and Transition in Second Language Teaching Methodology. Working Papers in Educational Linguistics, 13(1), 1–22.
 
Schmitt, N. (2000). Vocabulary in language teaching. Cambridge University Press.
 
Schwartz, D. M. ( 1,2,3 ). (2014). Breaking Through Barriers: Using Technology to Address Executive Function Weaknesses and Improve Student Achievement. Applied Neuropsychology: Child, 3(3), 173-181–181. https://doi-org.ez.xjtlu.edu.cn/10.1080/21622965.2013.875296
 
Webb, S. (2007). The Effects of Repetition on Vocabulary Knowledge. Applied Linguistics, 28(2), 46–65. https://doi.org/10.1093/applin/aml048
 
Wong, C. H. S., Tsang, K. C. K., & Chiu, W.-K. (2021). Using Augmented Reality as a Powerful and Innovative Technology to Increase Enthusiasm and Enhance Student Learning in Higher Education Chemistry Courses. Journal of Chemical Education, 98(11), 3476-3485–3485. https://doi-org.ez.xjtlu.edu.cn/10.1021/acs.jchemed.0c01029
 
Zhu, D. (2020). Programming of English Word Review Planning Time Based on Ebinhaus Forgetting Curve. 2020 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), Intelligent Transportation, Big Data & Smart City (ICITBS), 2020 International Conference on, ICITBS, 901–904. https://doi.org/10.1109/ICITBS49701.2020.00199
 

AUTHOR
Lulu HUANG
Associate Language Lecturer
English Language Center
School of Languages
XJTLU

DATE
14 March 2024

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