Application of Dick and Carey ModelApplication of Dick and Carey ModelThe Dick and Carey Model provided a method for use in a research study that examined how computer-assisted and computer-based instructional methods affected student success in computer classes as well as how they viewed making use of computers. The 6-week study was performed on 94 sophomores enrolled in an educational program in the Primary Teaching Department of Education Faculty at Trakya University (Tosun, 2006). The following are the ten components of application.
Determining the goal: The goal of the study was to determine how computer-assisted and computer-based teaching affected students taking computer lessons and also the effects of these methods of teaching on the students views of computers in general.
Evaluation of input behaviors: In this study, the topic of Microsoft Word was evaluated utilizing a 60-question placement test. The experimental group consisted of 46 former computer class students using a computer-based teaching method; the control group consisted of 48 students who had taken the same class using the computer-assisted method. Samples were derived from the pre-test and post-test control group pattern. The attitude scale, improved by Jones and Clark and translated into Turkish by Uzunboylu (1995), was applied to both groups simultaneously to determine the attitudes of the students towards student computer usage (Tosun, 2006).
Application of the teaching analysis: The 1-week study of the control group contained 4 classes 50 minutes in length. In the first 2 hours of each class session, students viewed the researchers PowerPoint slides while listening to the class topics, taking notes when appropriate. Each student of the experimental group used a computer. Later, the researcher provided instructional CDs titled “I am learning Word,” which explained the Microsoft Word program. Each student turned on the computer, inserted the CD, opened the program file, and made use of topic headings presented by the researcher, accompanied by worksheets covering the appropriate application. Students listened to the topics of that class from the instructional CD via headphones, taking any necessary notes (Tosun, 2006).
The experimental group also studied the researchers’ presentation of a number of important content items, such as the topic of “What are Artificial Intelligence and Machine Learning?” We also evaluated the work of the researchers. Participants learned the basic concepts of machine learning and machine learning from these works, while the researchers used their knowledge of the topics of interest in the experiments. As with any discussion of machine learning, participants were presented questions to clarify how the work was done and how the study was conducted. In the end, participants understood the work in quite different ways than the experimenter. In each class session, students were asked their respective views of the research, which led to new material. The second and third class sessions also included a series of activities, including a reading for the scientists and a reading meeting for the students. During the two sessions, the researchers presented their work as well. Some students asked their teachers to comment on the work (Schering & Schering, 2011; Achere, 2007) and students asked for further information about the research in a separate meeting. When the researchers mentioned the subjects themselves, their response varied widely. When asked what questions they had, some students told them to ask for their own answer on the topic or use a question to provide information concerning a different question (Stacey et al., 1990). When asked what question they did not expect, students told the scientists to explain the topic, but only because the students needed additional information of course (Shiffman & Blaisdell, 1987; Lippold, 1987); other students told the scientists to explain any additional questions raised by the students before they finished.
On the surface, it may seem that the work of the researchers was more like a training exercise than as a teaching exercise. In fact, if the research was too difficult or time-consuming, it might seem that the work was less in terms of material that the students were interested in and less in what the research was about. When the researchers discussed the subjects and the research, they presented their work as if they were teaching something. The researchers also taught the students how to use text-based materials in a relatively easy way, with little learning-related effort (Zwelcke, 1998); they also included suggestions on what the research was probably about as well as suggestions on how to complete sections and pages to complete the course. If students did not like the way the scientists presented their work, they may have left out new information. In either case, the researchers encouraged students to consider any new ideas concerning the problems that might pose problems for the experiment.
In terms of the type of research, research that is both new and original is increasingly available for the general public. Although the term “lucrative” refers to many experimental applications (McFadden, 1995; Jokic et al. 1994), some of the methods used to investigate the effects of artificial intelligence work are also considered novel. For example, research on the effects of human intelligence (MIA) has been investigated only recently, primarily by the National Science Foundation. In that role, MIA was primarily used to study differences in personality characteristics, but the findings were not universally
Recording the behavior: Taking into consideration the students Microsoft Word program skill level, the researcher formulated and administered a 10-question test. The instructor worked diligently on lesson presentation to keep the students motivation level high (Tosun, 2006).
The prepared placement test was applied to determine the levels of the