Research Methods Assignment Sample

• Type Assignment
• Downloads534
• Pages12
• Words2896

Introduction to Research Methods Assignment

The methods section of this experimental research report includes a description of the procedures and analytical techniques utilized in this particular research. This includes the description of participants, study design, material used, and research procedure. Additionally, the structure of this section aligns with academic standards often referenced in Online Assignment Help UK, ensuring clarity and precision in reporting methodological approaches.

Participants

The number of samples used in this study was 46 participants. In this experimental study, the data have been collected from these 46 participants. It means that the sample size of this experiment was n = 46. Among these participants, 40 (n = 40) were female, while 6 (n = 6) of them were male participants. The participants' age group was in the range of 22 to 65 years (M = 35.3 and SD = 10). It means that both young and old people were present in the group of participants. The total number of native English speakers among these participants was, however, the number of native English speakers 32. The educational qualifications of these participants were graduated from high school, college, university postgraduate students, etc. These 46 participants were from 15 total countries. These countries were Hungary (n = 4), Netherlands (n = 2), Poland (n = 4), South Sudan (n = 1), Sweden (n = 3), Italy (n = 1), New Zealand (n = 3), Cayman Island (n = 1), Greece (n = 2), Iceland (n = 1), Ireland (n = 2), Portugal (n = 1), South Africa (n = 2), Trinidad (n = 40) and United Kingdom (n = 18).

Design

This particular research work contains the development of an experimental study. This study includes descriptive statistical tests and the use of one-way ANOVA in SPSS software (Purwanto, 2021). The cross-sectional participant group becomes very important for the understanding effect of mind wavering on an individual’s comprehension capabilities. Based on this research rationale, the current assessment used experimental research design and designated mind-wandering and comprehension as the two variables of interest. The cross sectional design of the assessment enabled the evaluation of the participants at a given time thus having a view of the impacts of mind-wandering on comprehension. Descriptive statistics and the one-way Analysis of Variance (ANOVA) were used to analyse the data through the SPSS software (Trasmundi & Toro, 2023). One-way ANOVA was particularly important in comparing the comprehension scores across different conditions of mind wandering accordingly determine any significant performance differences as informed by level of intentional or unintentional mind wandering. This design helps the theory to be tested fully and helps in the establishment of the causal factors.

Materials

The entire data collection process was performed in the Gorilla Experiment Builder platform. To collect the data from human participants, this study received ethical approval from the “University Research Ethics Committee (REC)”. The participants used their electronic devices such as mobile, iPads, and laptops and access to the internet. An information sheet, a consent form, demographic questions, and also four sets of academic texts and associated questions were given to the participants. These were the materials used to collect the required information from the participants.

Procedure

The data collection procedure of this study includes the formation of four sets of academic texts of questions. Two of these texts were easy and two were difficult. The understanding of the academic writings was done by unintentional and intentional mind-wavering by the participants. For example, participants were told to change their minds into other thoughts, intentionally and unintentionally. If the answers of participants were correct then they got 1 point while wrong answers provided 0 points.

The overall scores of the participants were taken into an Excel sheet. Then these data were further analyzed in the SPSS data analysis tool (Mustafy & Rahman, 2024). In SPSS, the use of descriptive and inferential statistics tests such as one-way ANOVA.

Results

The findings from the SPSS software are presented in this particular section of this research report. These results include descriptive statistical calculation of participants’ test scores and a one-way ANOVA test.

Table 1: Descriptive statistics of the Test Scores of participants

(Source: Self-created in SPSS)

From this above-mentioned data table (SPSS output), the mean, min/max values, standard deviations, and the sum of each independent variable can be observed properly (Mitra, 2023). This particuler experiment aimed to identify the impact of test conditions on participants’ test scores. The mean and standard deviation of these independent variables are Difficult Intentional (55.07, 27.757), Difficult Unintentional (56.33, 24.528), Easy Intentional (51.8, 25.143) and Easy Unintentional (52.37, 26.141).

Table 2: ANOVA output of Test_Score_lV1 (Difficult Condition)

(Source: Self-created in SPSS)

Table 2 contains the findings of the one-way ANOVA test from the SPSS software. It was used to find out whether intentional and unintentional mind wavering can reduce the test scores of participants or not in difficult conditions. The ANOVA test value is estimated at 0.053. In this aspect, the independent value related to mind-wandering situations do not come to view to have a relevant effect on the dependent value connecting with comprehension values. The elevated p-value recommends that the differences monitored in different test values are more considerable due to random opportunities that to the experimental control related to mind-wandering (Robison, et al. 2020). The outcome applies that either the experimental control was not effective enough to obtain measurable variances in understanding related to the mind-wandering, as connected with the assessment, does not effectively impact understanding. This research highlights different queries recommending other components like difficulty related to various personal variances in the aspect of mental dependence, might contribute an effective role in this context.

Table 3: ANOVA output of Test_Score_lV2 (Easy Questions)

Research Methods Assignment Sample

Liked This Sample? Hire Me Now

Etta Branch 6 Years | MA

(Source: Self-created in SPSS)

Table 3 also holds the findings of the one-way ANOVA test from the SPSS software. It was used to find out whether intentional and unintentional mind wavering can reduce the test scores of participants or not in easy conditions. The ANOVA test value is calculated at 0.011. The significantly low score of F indicates that the difference between the classes signifies that these all are less differentiated to the difference within the groups. The score of p related to 0.916 far related to the traditional approach with a value of 0.05 for statistical relevance, applies that the variances assessed in the extension values over variation situations related to these independent values are effectively due to separate differences rather than any systematic impact related to different experimental control. These results directly conflict with the hypothesis that certain executive control conditions that involve mind wandering meaningfully damage comprehension (Zedelius, et al. 2021). These aspects stress the likelihood that the comprehension can be affected by other factors which could not be taken into consideration within the framework of the given experiment, which can be cognitive, attention, or simply a complexity of the texts used. These overall low effects of the independent variables imply that the association of mind-wandering and comprehension may be more intricate and could well be regimen by other variables not controlled in this study.

Discussion

The primary goal for performing this experimental research was to identify the relationship of mind wavering with the comprehension capabilities of a person. A hypothesis was developed that examined whether intentional and unintentional mind wavering can reduce the test scores of participants or not in difficult conditions (Jalolov, 2024). Another research hypothesis was whether intentional and unintentional mind wavering can reduce the test scores of participants or not in easy conditions (Seli et al. 2016). To find out the accurateness of these two research hypotheses, the one-way ANOVA was completed in the SPSS software (Wang, 2021). In difficult test conditions, the ANOVA outputs for intentional and unintentional test scores were identified as 0.053, at a significance level of 0.818. The p-value for this particular ANOVA test was identified as 0.818. It ultimately means that within the intentional and unintentional mind-wavering test scores, there are no significant differences is found.

In easy test conditions, the ANOVA outputs for intentional and unintentional test scores were identified as 0.011, at a significance level of 0.916. The p-value for this particular ANOVA test was identified as 0.916. This particular result was found to have a much higher significance level than the normal p-value which is 0.05 (Sen & Yildirim, 2020). Here, this result also shows that there is no significant differences were found between the intentional and unintentional mind wavering test scores.

However, the descriptive statistics table presented in Table 1 has shown that the development of the highest mean group was in difficult test conditions. On the other hand, the lowest mean group was shockingly observed as the group with easy test conditions. It was identified that the development of the previous studies' results on this research area have shown different understanding (Feng et al. 2013). However, it become very effective for the understanding of two types of mind-wavering types on the comprehension abilities of individuals.

In this particular research, the collection of data was done from a total number of 46 participants which includes both male and female participants. On the other hand, the data collection techniques that were utilized in this particular research were associated with the formation of academic questions. All of the participants in this research were given two sets of academic writings with multiple questions. These given academic writings were categorized into two different groups which were easy and difficult. The difficulties of these questions were previously identified, before giving them to the participants. The test scores were formed based on the accurate answers given by the participants. Their correct answers gave them 1 score point and wrong answers gave them 0 points. Apart from these difficulty levels of questions, another task condition was formed which was the intentional and unintentional mind wavering of these people.

The insights related to the descriptive statistics delivered in the insight table provide vital information into how various examination conditions which are classified as difficult and tough intentional and easy intentional along with easily intentional impact correspondents’ examination scores. By evaluating the average, minimum, maximum, total, and SD, it is assessed the overall styles and differences within the effective collection of insights, which are vital for explaining the outcomes related to the experiment (Pan, et al. 2020). The average scores for every situation highlight the mean performance related to the correspondents under every aspect of the experiment. For the tough intentional situation, the average variable is 55.07 connected with SD with the value of 27.57 highlighting a significantly extended dispersion across the average. Considerably, the tough unintentional situation has a little elevated average score with a value of 56.33 connected with a lower SD value of 24.528. This recommends that while the performance of correspondents in the situation was a little bit better on mean, the values were somewhat more continuous contrasted to the tough intentional situation.

However, Easy Intentional as a condition had a comparatively lower mean of 51. 8, standard deviation, 25. 143 which can be described as moderate extent of spreading of scores. The results showed that the Easy Unintentional condition had slightly higher mean of 52 than Medium Unintentional condition. 37 with standard deviation of 26. 141. That is why the basic fact that the means of the Easy Intentional and Easy Unintentional conditions are rather close indicates that the ease of the task may have moderated the effect of intentional vs unintentional mind-wandering on comprehension (Chinchanachokchai, et al. 2020). From the ANOVA, there were no major differences between the means accordingly, the descriptive statistics will help to explain why there was no much variation. However, the standard deviations that are greater than 10 across all conditions apply variance observed in the learners depending on the instructional conditions despite the means scores. This is might have covered any existing impact of mind-wandering on comprehension, because comprehensions may have depended on other factors apart from mind-wandering such as, individual differences in cognitive capacity, attentiveness or subject familiarity. This interpretation that could be given to these findings is that mind-wandering might not necessarily be a theory of comprehension disruption as this is assumed in the hypothesis.

The small differences in the means between the intentional and unintentional conditions, especially in the easy items, give the impression that participants’ understanding may not be easily compromised by mind-wandering especially when the subject matter is easy. This strength could be attributed to the fact that the participants were able to sustain their attention in compensating for their mind-wandering or the component of the task where participants entirely completed the easier tasks comprehensively that they became engaging (He, et al, 2023). Furthermore, the obtained relatively large standard deviations across all conditions indicate that participants explain large variability in their mind-wandering related responses. Some participants might use better ways of tackling mind wandering, in that they could either re-engage their attention instantly or just possibly have a higher original level of comprehension loss due to distractions. These individual differences might have masked the impact of the experimental manipulations thereby resulting to the non-significance of the ANOVA results obtained.

The second important factor, which should be taken into consideration is the role of the task difficulty in the connection between mind-wandering and comprehension. In simple terms, the performance of the participants on average was slightly higher in the difficult conditions than in the easy conditions, and this may be because the tough conditions that the material posed to participants made them use more of their brain power, thus leaving no chance for them to day dream. On the other hand, the lower mean scores in those conditions could be attributed to the potential of the less difficult tasks to elicit mind-wandering as those tasks posed less demands on the participants’ cognitive resources (Stanley, et al. 2022). But through the two tests of ANOVA, it was revealed that both the task difficulty level and the condition of mind-wandering did not significantly affect comprehension. This could mean that there is a more complex correlation between mind-wandering and comprehension than what has been seen earlier. For example, the characteristics of the mind-wandering. To be more specific, there could be aspects of mind-wandering that were not captured in this study and could be more relevant such as the timing of the mind-wandering episodes whereby mind-wandering can occur at some critical therefore, the descriptive statistics in combination with the results of the ANOVA give an insight into the experiment’s results.

There were evident variations in mean scores with reference to the different test conditions However the variations were not significant, it was thus found that the effects of mind-wandering on comprehension are not entirely clear-cut. Future studies could expand on future research by looking more closely at the nature of mind-wandering including its content, duration or timing so as to understand it impact on comprehension. Moreover, the efforts in exploring differences in cognitive methods and coping with the interferences may provide more information as to the relationship between mind wandering and understanding.

Reference List

Journals

• Addison, C. C., & Jenkins, B. W. C. (2023). Data Analysis Using SPSS: Jackson Heart Study. In Statistical Approaches for Epidemiology: From Concept to Application (pp. 363-379). Cham: Springer International Publishing. [Retrieved From: https://link.springer.com/chapter/10.1007/978-3-031-41784-9_21][Retrieved On: 25.08.2024]
• Chinchanachokchai, S., Duff, B. R., & Faber, R. J. (2020). Distracted mind: the effects of multitasking and mind wandering on consumer memory for ad content. International Journal of Advertising, 39(5), 631-654. Retrieve from: https://www.researchgate.net/profile/Sydney-Chinchanachokchai/publication/336140822_Distracted_Mind_The_Effects_of_Multitasking_and_Mind_Wandering_on_Consumer_Memory_for_Ad_Content/links/5f369964458515b7291f3b36/Distracted-Mind-The-Effects-of-Multitasking-and-Mind-Wandering-on-Consumer-Memory-for-Ad-Content.pdf Retrieved on: [25.8.2024]
• Feng, S., D’Mello, S., & Graesser, A. C. (2013). Mind wandering while reading easy and difficult texts. Psychonomic bulletin & review, 20, 586-592. [Retrieved From: https://link.springer.com/article/10.3758/s13423-012-0367-y][Retrieved On: 25.08.2024]
• He, H., Chen, Y., Li, T., Li, H., & Zhang, X. (2023). The role of focus back effort in the relationships among motivation, interest, and mind wandering: an individual difference perspective. Cognitive Research: Principles and Implications, 8(1), 43. Retrieve from: https://link.springer.com/content/pdf/10.1186/s41235-023-00502-0.pdf Retrieved on: [25.8.2024]
• Jalolov, T. S. (2024). ANALYSIS OF PSYCHOLOGICAL DATA USING SPSS PROGRAM. Multidisciplinary Journal of Science and Technology, 4(4), 477-482. [Retrieved From: http://mjstjournal.com/index.php/mjst/article/view/1419][Retrieved On: 25.08.2024]
• Mitra, A. K. (2023). A Step-by-Step Guide to Data Analysis Using SPSS: Iron Study Data. In Statistical Approaches for Epidemiology: From Concept to Application (pp. 343-362). Cham: Springer International Publishing. [Retrieved From: https://link.springer.com/chapter/10.1007/978-3-031-41784-9_20][Retrieved On: 25.08.2024]
• Mustafy, T., & Rahman, M. T. U. (2024). SPSS. In Statistics and Data Analysis for Engineers and Scientists (pp. 135-180). Singapore: Springer Nature Singapore. [Retrieved From: https://link.springer.com/content/pdf/10.1007/978-981-99-4661-7.pdf][Retrieved On: 25.08.2024]
• Pan, S. C., Sana, F., Schmitt, A. G., & Bjork, E. L. (2020). Pretesting reduces mind wandering and enhances learning during online lectures. Journal of Applied Research in Memory and Cognition, 9(4), 542-554. Retrieve from: https://www.researchgate.net/profile/Steven-Pan-4/publication/347120870_Pretesting_Reduces_Mind_Wandering_and_Enhances_Learning_During_Online_Lectures/links/5fe531a245851553a0eadbf6/Pretesting-Reduces-Mind-Wandering-and-Enhances-Learning-During-Online-Lectures.pdf Retrieved on: [25.8.2024]
• Purwanto, A. (2021). Education management research data analysis: comparison of results between Lisrel, Tetrad, GSCA, Amos, SmartPLS, WarpPLS, and SPSS for small samples. Nidhomul Haq: Jurnal Manajemen Pendidikan Islam, 6(2). [Retrieved From: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3982753][Retrieved On: 25.08.2024]
• Robison, M. K., Miller, A. L., & Unsworth, N. (2020). A multi-faceted approach to understanding individual differences in mind-wandering. Cognition, 198, 104078. Retrieve from: https://www.sciencedirect.com/science/article/am/pii/S0010027719302513 Retrieved on: [25.8.2024]
• Seli, P., Risko, E. F., & Smilek, D. (2016). On the necessity of distinguishing between unintentional and intentional mind wandering. Psychological science, 27(5), 685-691. [Retrieved From: https://journals.sagepub.com/doi/abs/10.1177/0956797616634068][Retrieved On: 25.08.2024]
• Sen, S., & Yildirim, I. (2022). A tutorial on how to conduct meta-analysis with IBM SPSS statistics. Psych, 4(4), 640-667. [Retrieved From: https://www.mdpi.com/2624-8611/4/4/49][Retrieved On: 25.08.2024]
• Stanley, M. L., Whitehead, P. S., Marsh, E. J., & Seli, P. (2022). Prior exposure increases judged truth even during periods of mind wandering. Psychonomic Bulletin & Review, 29(5), 1997-2007. Retrieve from: https://link.springer.com/content/pdf/10.3758/s13423-022-02101-4.pdf Retrieved on: [25.8.2024]
• Trasmundi, S. B., & Toro, J. (2023). Mind wandering in reading: An embodied approach. Frontiers in human neuroscience, 17, 1061437. Retrieve from: https://www.frontiersin.org/articles/10.3389/fnhum.2023.1061437/pdf Retrieved on: [25.8.2024]
• Wang, G. (2021, September). Application of SPSS Data Analysis in Moral Teaching of College English Course. In 2021 4th International Conference on Information Systems and Computer Aided Education (pp. 183-188). [Retrieved From: https://dl.acm.org/doi/abs/10.1145/3482632.3482670][Retrieved On: 25.08.2024]
• Zedelius, C. M., Protzko, J., & Schooler, J. W. (2021). Lay theories of the wandering mind: Control-related beliefs predict mind wandering rates in-and outside the lab. Personality and Social Psychology Bulletin, 47(6), 921-938. Retrieve from: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/154300/acp3632.pdf?sequence=2 Retrieved on: [25.8.2024]