Using audience response systems (clickers) results in positive outcome - Research Paper Example

THE USE OF AUDIENCE RESPONSE SYSTEMS (CLICKERS) RESULTS IN POSITIVE OUTCOME The Use of Audience Response Systems (Clickers) Results in Positive Outcome 1. The use of clickers in large classes initiated better student performance through much more dynamic and interactive techniques in learning chemistry and biology. A study conducted twice in 2005 in an introductory biology class taught by the same instructor assessed whether using clickers could help them improve test scores at the end of the semester (Freeman, et al., 2007). Compared with the scores of classes in 2003 by the same instructor, the positive effects of using of clickers and increasing intra-class interactions were significant, and students in the 2005 clicker sections attended classes much more frequently and had higher exam score averages than in 2003 classes, attributed to the incentive of earning additional points to improve class grade along with more class interactions.

However, compared with exam scores of card users in the same academic year of 2005, the differences in their exam scores were found to be non-significant (Freeman, et al., 2007). Another study in 2008 produced similar results in general chemistry classes (Hoekstra, 2008). Anxiety-levels associated with the course were also lessened and cooperation and interaction between students increased, but the latter two elements were found out to be affected by gender, suggesting that females are much more likely to cooperate with others for answers as opposed to males.

The study had similar conclusions that increased interaction among classmates can improve lesson retention and exam scores when compared with traditional and passive learning settings (Hoekstra, 2008). In relation to clicker use, attitudes of chemistry instructors to clicker use were affected by how long they were teaching the subject, as well as the nature of the type of students that they teach (Emenike & Holme, 2012). Younger instructors and those holding undergraduate introductory classes were much more likely to give positive feedback on clicker use, compared with older instructors and those holding graduate and higher courses or teaching advanced undergraduate courses.

The research concluded these along with the idea that clicker use among chemistry instructors was still in its early adoption stages, as there were still a lot more that prefer traditional teaching methods over clicker use, and younger instructors are more agreeable to use clickers for their classes compared to older ones due to their different approaches in teaching the subject, suggesting a chasm that prevents rapid adaptation of clickers in chemistry courses (Emenike & Holme, 2012). The three researches did not have too much setbacks, and each used considerably large sample populations (n=3338, n=2000~, n=1500~ respectively), however the third research mentioned a drawback on the survey questions and this prevented the association of clicker use on its effectiveness ratings. 2. Can the use of clickers improve mid-term and final examination scores in introductory courses among students in interactive classes compared to students in traditional and passive learning settings? 3. Based on the assumptions that increased class interactions and class participations could improve exam scores and understanding of the subject, it is hypothesised that the use of clickers in introductory courses could create significant differences on the overall scores in mid-term and final exam score results in general chemistry and biology courses having clickers and increased student interactions, compared to non-interactive and traditional class settings. 4. Independent variable for the experiment would be clicker usage in class, and the dependent variables would be the mid-term and final exam scores in the introductory biology and chemistry courses.

The resultant data for the experiment would be nominal data. 5. Target populations would be those taking introductory biology and chemistry courses, four classes each, and handled by the same instructor who willingly participated for the test, thus a total of four classes, two traditional classes and two clicker classes per subject, and is somewhat patterned to the experimental design previously mentioned (Freeman, et al., 2007). Classes that will undertake clickers for instruction and traditional classes will be assigned randomly, and while all members of the class will be informed about the research, the participants for each class whose data will be used shall be selected using a class list and a random number generator.

After assigning the random numbers and ranking these from highest to lowest, the upper 70% and their data shall be selected for the research. The same setup will be used for the next semester and for the same chemistry and biology instructors. 6. Participants shall be exposed to the clicker as an independent variable in the beginning of classes, and it will be explained to them that clickers shall be used to gauge student’s skills during graded multiple-choice questions posed by the instructor (maximum of two per session), as described in Freeman et al. (2007). The instructor will allow students to form small groups to answer the clicker questions, but will also allow for independent problem solving, after which the correct solutions to the problems shall be presented after the whole class has finished.

The previously-selected students’ scores for mid-term and final exams will be obtained from the instructors and encoded to find the mean and SD. For traditional classes, apart from selecting the upper 70% in ranking, the independent variable shall not be applied but the mid-term and final exam results shall be obtained from the same instructor to find the mean and SD. 7. As mentioned in the previous number, data selection is based on ranking the generated random numbers assigned to students and selecting the upper 70%, despite informing the whole class about the experiment so as not to affect everyone’s performance in class.

This should also account for possible sources of error such as students that drop out or cheat in class, and their data shall be discounted from the data analysis, as also mentioned in Freeman, et al. (2007). Methods for testing shall use basic null hypothesis statistical testing to assess the effects of the individual and independent variable. The basic assumption for the experiment is that classes with clickers would generate significantly higher mid-term and final exam scores than the classes using traditional learning methods.

The alternative hypothesis assumes that there would be significant differences between the clickers and non-clickers using p=0.05, using 80% power data generated are reliable, and the means lean toward rejecting Ho (clicker classes have no effect). If ANOVA could generate p=