Introduction

Social networking has developed in attractiveness among college learners over the years. It’s a technique to build relationships with people in and out of the learning institution. Many students use social networking to feel as if they are a part of a community. When it comes to social networking, smartphones have become a new source of concern for academics. A smartphone is a mobile telephone that “allows users to select the programs they wish to install” whereas also serving as a communication and computer device (Stollak, 2011). According to a survey conducted at Ball State, the number of smartphones acquired by students had doubled in the previous year.

Cell phone usage is common among college students in our time; according to studies, it is detrimentally related to academic success. It influences learning and accomplishment both in out of class intellectual appointments. Several research has looked into the link between entire daily cell phone usage and college success. There is also a substantial negative link between students’ estimations of average daily text messaging use and their college grade point average. (Harman & Sato, 2011). Similarly, Jacobsen and Forste discovered that over the span of three days, participant’s who were consumed by social media sites as well as excessively using their devices for calls and/or messages had negatively predicted college grade point averages. (Bjornsen & Archer, 2015). According to the authors, 62% of their participants claimed they used non-academic devices in class, while learning, or while doing assignments.

College and university teachers believe student cell phone use in class hinders the concentration on learning and attentiveness compared to normal communication, data collecting, amusement pursuing, social networking culture and practices of college students. Therefore, in this study, we intend to investigate the best interventions for reducing cellular device use of college students. According to the article, “The Effects of Using a Conditioned Stimulus to Cue DRO Schedules,” when their student would wear a bracelet, and if she did not engage in the behavior at all during a duration of time, the bracelet was removed and she was free to engage in the behavior they wanted to reduce. They would slowly increase the interval duration to get the student to engage in the behavior less. (Fellman, Taylor, 2015). This intervention was circling around DRO while utilizing a visual cue of when she was allowed to engage in the behavior and when she was not able to. Another study on a useful DRO schedule and even a VMDRO schedule was in an article titled, “Reducing Covert Self-injurious Behaviors Maintained by automatic reinforcement through a variable momentary DRO procedures” where they are conducting a study on treating self injurious behaviors with the use of DRO procedures. A 12 year old was placed in a room, and everytime the therapist would come check on him and he was not picking in that interval, he would receive praise and a token on his board. If he did pick in the duration of time, she would walk in and say nothing. They eventually increased the duration interval to see if it would decrease the picking behavior (Tiger, Toussaint 2013). This example also shows the process and effectiveness of DRO procedures. Using the science from applied behavior analysis, we hypothesize that this problem could be addressed by utilizing a DRO schedule of reinforcement to reduce cell phone usage, but not completely cut off access in order to gradually increase the amount of time spent away from cell phones. 

Methods

Participants 

Participants chosen for this study included 5 CSU Stanislaus students between the ages of 18-25. Participants included 3 female identifying and 2 male identifying students of various ethnic groups and socioeconomic statuses. Researchers chose to focus the study on students who seek to pursue a masters degree after completing their undergrad with a concentration in psychology. All participation was voluntary. 

Setting and Sampling Procedures 

Our participants will be chosen similarly to how students for the Harrison and Pyles (2013) article chose their participants; by letting them come to us. We plan to post on the Psychology major forum on canvas explaining our study and what it will entail. We will post on the Psych forum to limit this to psychology majors since this may be of more interest to them.. We do not have a specific setting/location for the study because it will be based on wherever the participants will be. The participants will be able to track their cell phone usage by the utilization of their cell phone’s app that tracks how many hours were spent on their phones each day. We will have them submit their daily usage stats to us until the study ends and hopefully we will see a decrease. We will also ensure and disclose all agreements to maintain safety and ethical guidelines. We will make sure there is fair subject selection by telling our psych forum about the study and allowing them to volunteer to be a part of this study. This way we can get a decent mix of participants for our population from different backgrounds, genders, religions, and so forth. We will also make sure that there is a favorable risk-benefit ratio by reassuring our participants that no dangerous acts or health hazardous activities will be asked of them. In fact, reducing their usage would be more of a health benefit to our participants. With all this in mind, we plan to keep our study within the agreements of the ethics board. 

Materials

The materials used in this study consist of a survey, a rating scale, and the usage tracker incorporated within each participants’ phone. First, we will collect the data from the cell phone usage tracker to assess each participant’s initial phone usage. We will observe the usage tracker every week once the participant receives the notification for it. Second, we will provide a survey to the participants to record any obstacles they may have faced during the study. Said obstacles may contain emergencies, broken phones, late phone bills, or anything other difficulties or inconveniences the participants may have experienced. Third, we will provide a rating scale at the beginning of the study and at the end of the study, to record the participants’ feelings of their phone usage and productivity. This rating scale will have a 1-5 scale, with 1 being Not So Productive and 5 being Very Productive. With these materials, we will gather enough data to evaluate our study.

Procedures

 Measurement

Dependent variable measures are the college student ‘s academics. Everytime the participants went on their phone throughout the day their phone usage application kept track of time they spent on their phone and percentage per app of the total time spent. 

Independent Variable

Independent variable is the amount of hours, the hours in the case of our study is what would be directly affecting the participants’ academics. The application tracks even down to what application was used and at the end of the week averages out by percentage. Due to the new level of awareness the participants would lessen their phone usage.

Experimental Design

DRO, Differential Reinforcement of Other behaviors was used to assess and record students cell phone usage. The purpose is to encourage the students to monitor their phone usage more closely in efforts to exchange that time to work on their academics and compare academic grades of those who had more and those who had less phone usage at the end of the study.  Reinforcement in this case is academic improvement. 

We gathered the Psychology major participants by posting on the Canvas forum for Psychology majors

Once we had the participants we let them live their daily lives and report their cell phone usage at the end of each day. 

The time frame of this study was about four weeks.

 We compared the difference in academics and phone usage from the first week to the fourth.  

Results

Figure 1: Design Graph showing phone usage in four weeks for Participant 1

Phone usage for the first participant decreases from 268 to 173 minutes per day. These values are stagnant for phase one between eighth and fourteenth days. Each day indicates a drastic decrease in using the phone for this participant.  

 

Figure 2: Design Graph showing phone usage  in four weeks for Participant 2

The second person shows a reduction in the use of communication devices from 328 to 217 minutes in the four weeks. In the second stage, the benefit remains constant at 273 minutes per day.

 Figure 3: Design Graph showing phone usage  in four weeks for Participant 3

Participant 3 has the highest phone usage of 345 minutes which reduces daily for the next 28 days. The sharp decrease is evident in all three phases.

Figure 4: Design Graph showing phone usage  in four weeks for Participant 4

 

Figure 4 displays the phone use for the fourth participant, which decreases from 189 to 128 minutes daily. However, on day 27, the time is 124, which rises to 128 minutes on the last date.

Figure 5: Design Graph showing phone usage  in four weeks for Participant 5

 In figure 5, the student’s phone use decreases from 127 minutes to 74 minutes. According to this data, participant five has the highest decrees of phone usage for the four weeks. Therefore, the cellular device affects the students’ academic performance. 

A decrease in using this electronic communication device indicates an increase in academic performance. Participant three has a high use of phones hence low in school academics. However, in terms of usage per day, the individual decreases by 111 minutes compared to 53 minutes in figure five. In that case, cellular device use is directly proportional to academic results from this information.

Discussion 

As Figure 1 suggests, there are days when the use of the phone was stagnant as there are no notable changes. However, there are days when the variations are notable and widespread. It is fair and worth noting that the phone use as the month begins for this participant is high. A logical explanation for these changes is that schoolwork was demanding as the month progressed. Thus, the participant had to dedicate more time to their studies, limiting cell phone usage.

In the case of Figure 2, more drastic changes are noted in the three phases. In the first phase, the usage of cell phones was high. However, there was a drastic decline in the two phases that followed. There were externalities and secondary factors that influenced the sudden behavior change. These forces indicate that changes in cell phone usage emanate from the participant’s increased commitment to their studies. Thus, schoolwork was a likely factor that consumed more of their time, necessitating the limited usage of their cell device. Thus, the increased commitment to their studies is bound to impact their academic performance positively.

Similar to the second participant, there is also a drastic change in the use of cell phones. As Figure 3 highlights, the alterations could emanate from the increased schoolwork and commitment. Cell phone use was a practice that was intense with this participant. Thus, the extreme changes indicate a variation in how the participant spends their time as other commitments have to be prioritized. These commitments are time-consuming as the participant does not have sufficient time to explore their phones. Also, the increased commitment to their studies is bound to impact their academic performance

Figure 4 and Figure 5 also highlight a drastic change in cell phone use. Compared to the baseline, the participant’s use of the cell device decreased as the weeks progressed. Their academic duties were demanding based on this trend. They took a lot of time from the student, which compelled them to change their time use as they rarely use the phone devices. The increased commitment to their studies is bound to impact their academic performance positively.

The post Introduction Social networking has developed in attractiveness among college learners over the appeared first on PapersSpot.