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«Item type text; Electronic Dissertation Authors Goertler, Senta Publisher The University of Arizona. Rights Copyright © is held by the author. ...»

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3.8.2.6 Classroom Observations For the same reason that the self-report forms were administered, I conducted monthly chat classroom observations for each class during approximately every third chat session. During that time, I took detailed notes about the interactions in the physical space, and also about the resources students consulted. Since I did not know the identities of the students and only created nicknames for them for the purpose of my data collection, the observations do not match perfectly with the transcripts. For example, one sample note is, “Girl who never types is just staring at her screen again.” While I know what the girl looks like, I do not know which screenname is hers, preventing me from identifying her in the chat transcripts in order to try to understand why she never typed.

Naturally, over the course of my observations, I learned some of the screennames, but not all of them. This issue could have been avoided by setting up different requirements with the Human Subjects Board.

The focus of the observations was to understand how much assistance the teacher was providing in the physical environment and how much the students were relying on each other’s help in the physical environment. With the help of the observations, I was also able to assess how many students used online resources, such as online dictionaries and internet translators, and how many students relied on their dictionaries or textbooks for assistance with the vocabulary.

The design of the lab encourages student collaboration and provides easy access for the teacher to assist students. These special features of the lab most likely influenced the interactions in the physical environment.

During the observations, it became apparent that it was important to note when the students called for the Lab Assistant rather than the teacher for help. The intended role distribution between the two is that the teacher is in charge of all teaching-related issues, while the Lab Assistant assists the teacher in using the technology if she needs it, and assists students with technological problems when necessary. Some of the teachers who use this lab explicitly state this role assignment to their students at the beginning of the semester. To my knowledge there was no such explanation made to the students by either EveningTeacher or MorningTeacher.

During my observations, I sat at the end of the room so that I had the opportunity to see a few screens on all three pods, all students, the teacher, and the Lab Assistant. I usually sat down right to the Lab Assistant when present which resulted in the students associating me as part of the tech team. When students asked me for help, I usually directed them to the teacher or the Lab Assistant. When the teacher asked me for help, I did provide assistance, but only when the teachers made mistakes in starting the technology did I intervene. No interventions were made as a result of incorrect interpretation of the activities or teaching decisions considered inappropriate by me from a teacher trainer perspective.

3.9. Summary In summary, this research study consisted of a background study and the main study. The background study informed the coding of the data of the main study, and provided information for the Teacher’s Manual. The main study is intended to understand the role of the teacher during chat and its effect on the students’ experience and learning.

For this study, three third-semester German courses taught by two teachers with varying levels of technological support were investigated. Due to their differing comfort levels in using computers for instructional purposes, the teachers were named MorningTeacher and EveningTeacher. The courses were labeled according to the technical support, with MorningTeacher’s courses being No-Support-Class and Some-Support-Class, and EveningTeacher’s course being Expert-Support-Class. Over the course of a semester, students and teachers engaged in almost weekly chat activities closely connected to the materials used during regular class time.

To find information about the participation and feedback styles of the teachers, and the students’ attitudes, learning, and experience, the following data sets were collected: pre-and post tests, pre-and post-surveys, self-report forms, classroom observation notes, chat transcripts, and chat analysis sheets. The data were analyzed in quantitative and qualitative fashions. Gain scores on the test were calculated. Pre- and post-surveys were analyzed, looking at numerical trends as well as a categorization of comments. Information from the self-report forms and classroom observation notes were used to describe the implementation more thoroughly. Chat transcripts were used for quantitative and qualitative analyses to identify patterns between the teacher’s participation and the students’ learning, and between error type and feedback type.

In this chapter, the research questions were presented along with the analysis procedures and the instrument descriptions (for a quick overview see table 3.7.). In the following chapter, the research results from each instrument will be presented along with a discussion of the results in relation to each other in order to answer this study’s research questions.

Table 3.7.

Data Types and Collection Methods

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4.1 Introduction In the previous two chapters, the theoretical background, the previous research, the research methods, the subjects and the instruments in this study were discussed. In this chapter, the results from the research in response to the research questions will be discussed. As has been mentioned in chapter three, the research questions are answered using multiple data sets, and the data sets are used to answer different questions.

Therefore, in this chapter, the research results from each data set will be discussed in detail in the first question they apply to, and later will be referred back to when appropriate, as to avoid repetitive information. Some questions will only address the results from the six case study subjects selected, and others from all students. In the discussions it will be pointed out which data set is considered. In cases where all subjects are discussed, the case study subjects’ results will be highlighted by underlining them in the appropriate tables.

As mentioned before, this study employs a mixed design and multi-faceted data sets. The 46 study participants and the two teachers were expected to engage in weekly 20-minute chat sessions over the course of one semester. However, due to other curriculum constraints and technological problems, chat sessions and chat transcripts were fewer than had been anticipated.

NSC (No Support Class): Students were engaged in 2 to 9 chat sessions, with a median of 7 sessions and an average of 6.5 sessions (see table 4.1. below). Chat sessions lasted between 9 minutes and 16 seconds and 36 minutes and 20 seconds and an average of 24 minutes 43 seconds. On average students were engaged in 2 hours 44 minutes and 49 seconds of chatting over the course of one semester. This chat time is part of approximately 50 total hours of instruction over the course of the semester. As recorded in the classroom observations, a typical chat session in NSC can be described in the following manner: the teacher puts pieces of paper on the table that describe a chat activity and assign a channel; students walk in one after the other and sit down at a selfselected seat; students log into the program; due to students’ and teacher’s improper following of the procedures, computer problems are experienced often; since students come in at different times, some students are alone in chat rooms for a while; no Lab Assistant is present, hence the teacher assists in the physical space; students use online dictionaries, the textbook, and paper dictionaries as resources; students hardly ever talk to each other and if they do, the teacher comes over and asks them if they need help. This is a summary statement of the implementation of the chatting. Direct quotes from the classroom observations are in a following section.

SSC (Some Support Class): Students were engaged in 2 to 8 chat sessions, with a median of 6 sessions and an average of 5.88 sessions (see table 4.1. below). Chat sessions lasted between 6 minutes and 16 seconds and 43 minutes and 21 seconds and an average of 23 minutes 21 seconds. On average students were engaged in 2 hours 19 minutes and 4 seconds of chatting over the course of one semester. This chat time is part of approximately 50 hours of instruction over the course of the semester. Based on the classroom observations, a typical chat session in SSC can be described similarly to the NSC. There were only two differences observed: the students seemed to interact a little more with each other in the physical space, and a Lab Assistant was present. However, the Lab Assistant was often unable to fix the problems experienced.

ESC (Expert Support Class): Students were engaged in 3 to 10 chat sessions, with a median of 9 sessions and an average of 8.28 sessions (see table 4.1. below). Chat sessions lasted between 8 minutes and 32 seconds and 31 minutes and 8 seconds and an average of 19 minutes 58 seconds. On average students were engaged in 2 hours 46 minutes and 12 seconds of chatting over the course of one semester. This chat time is part of approximately 50 hours of instruction over the course of the semester. As noted in the

classroom observations, the following represents a typical ESC chat session:

EveningTeacher puts up the activities on the projector screen and explains the activity and unfamiliar words; but with occasional inaccuracies; group assignment is done by the Lab Assistant by handing out pieces of paper with a channel number, but he often assigns more students to a channel than was intended by the activity design; Lab Assistant instructs students in log-in and log-out procedures; students start chatting with each other;

students laugh and comment in the physical space; students read over each other’s shoulders; teacher sits down when chatting starts, and chats also, and comments out loud;

students calling for help are not always responded to; teacher plays music.

Table 4.1 Summary of Time Spent on Chat Activities by Class and Subject

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To summarize, chatting was implemented less often in the classes than initially expected. Furthermore, the chatting was implemented differently by the two teachers, with one seemingly encouraging and the other seemingly discouraging interaction in the physical space as modeled by the teacher’s behavior. Furthermore, group assignment was handled differently by the two teachers, with both approaches causing some pedagogical implementation problems, i.e., students alone in rooms in the NSC and SSC and too many students in a room in the ESC. Additionally, the three different classes received differing amounts of technical assistance.

To better understand the nature of the chatting, two case study subjects were chosen from each class to acquire an in-depth look at the interaction during chatting. A detailed analysis was undertaken for six transcripts sets, and they were analyzed to identify errors; corrective feedback; uptake; and patterns between errors and corrective feedback, errors and error uptake, and corrective feedback and uptake. The two students from each class were chosen based on their exposure to chatting. Since the chatting was only one small component in the class, it was thought that choosing the students with the maximum exposure to chatting would be the best indicator of how the students and teachers interacted and what potential effects the chatting may have. The following students were chosen: NSCDanielle and NSCJennifer, SSCEmily and SSCGina, and ESCAmanda and ESCVictoria. The names were changed to pseudonyms from their selfselected screennames. Furthermore, the class name was added to the pseudonym for ease of identification.

Table 4.2 Case Study Subjects

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NSCDanielle participated in 8 chat sessions for a total of 3 hours 37 minutes and 55 seconds during which she produced 939 words (i.e., 4.31 words per minute) and was exposed to a total of 89 words by the teacher (i.e., 0.41 words per minute). She is 19 years old and has studied Spanish in addition to German. She rates her German ability as “limited.” On the pre-test without the writing section, she received 46.75 points which ranked her 4th across classes, and on the post-test she received 52.75 points which ranked her 14th across classes. In her survey she reported appreciating the teacher’s feedback, but was critical towards peer feedback. Towards technology in the classroom she was favorable; however, she expressed caution in regards to the benefits of chatting for her spoken language ability. Furthermore, she stressed that chatting is only beneficial if the partners are accurate and fast.

NSCJennifer participated in 9 chat sessions for a total of 4 hours and 2 minutes and 43 seconds during which she produced 889 words (i.e., 3.66 words per minute) and was exposed to 80 words by the teacher (i.e., 0.33 words per minute). She is 18 years old and has studied Spanish and American Sign Language in addition to German. She rates her German ability as “decent.” On the pre-test without the writing section, she received

43.75 points which ranked her 5th across classes, and on the post-test she received 60.25 points which ranked her 3rd across classes. In her survey she indicated appreciating all kinds of feedback, and saw feedback by the teacher as a way of the teacher expressing that he or she cares about the students. In addition, she was favorable towards the computers in language classroom, as technology and learning feel like an inevitable part of the future. She also pointed out that she would be more likely to communicate with someone in Germany via the computer than in person.

SSCEmily participated in 8 chat sessions for a total of 3 hours and 34 minutes and 5 seconds during which she produced 1010 words (i.e., 4.72 words per minute) and was exposed to a total of 138 words by the teacher (i.e., 0.65 words per minute). She is 19 years old and has studied Spanish and French in addition to German. She rates her German ability as “that of a beginner.” On the pre-test without the writing section, she received 36 points which ranked her 15th across classes, and on the post-test she received



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