# data[].attributes.body
Read and Engage in DLL:

Choose ONE Theoretical/Methodological Piece (links on Canvas)

Morrison

Gopalan

Brady

Choose ONE Empirical Study (links on Canvas)

Li

Shirrell

Hemler et al

Find ONE Additional Empirical Piece Related to Your Interests

# data[].attributes.body
J: On top of summarizing and reflect about what Parsons (1937) said about empirical research and post-positivism, I started to wonder why these empirical research articles were assigned as week 4’s readings. Apparently these were not to educate us on the topic or content, then what’s the purpose of reading it? (Since I’m writing this even before Week 3 in-class session, I’m just guessing the reason- to be acquainted with the format of empirical research? Or to learn about what it means to conduct it?)

# data[].attributes.body
J: Aside from my question above, I think Kwok (2017) is very well-written in terms of communicating with its readers through the representation of data. It has every element of an empirical data and especially did a great job in displaying the findings.

# data[].attributes.body
I am not sure about the correlation vs causation part on p.37. First, the author did not explain how such research built correlation, if the p<.05, it has statistical significance. They also talked about SEM. SEM is regression, and what they call an experiment typically uses ANOVA. ANOVA and regression share the same statistical foundation, so I doubt the author in making that arbitrary distinction between correlation and causation. Correlation is the basis of regression, too. Second, you can still build causality in regression, if a factor is found to make a unique and significant contribution to explaining variances of the dependent variable, we can say this factor is causing a change. I think this is not a change in the research paradigm, it's just the development of statistical analysis appraoches.

# data[].attributes.body
One question I am having while reading the introduction is the premise. Is college attainment something desirable? or necessary? or a better choice compared to not attending college? I have a preference but i cannot assure you that works for everyone. This doubt came to be stronger when the author introduced the "rural advantage narrative" vs "rural disadvantage narrative". So depending on the narrator's standpoint, they may view something as problematic. This is also important that researchers need to "bracket" themselves and make sure they are faithfully reflecting and representing the participants ideas and needs.

After reading the full passage, yes I like it and it is similar to what we are doing. I like how they built models and explain factors in predicting variances of the dependent variable.

# data[].attributes.body
J: I don't think I understood his article thoroughly, but I do have one emerging question. On page 1, he said, "Knowledge is held to be an entirely quantitative affair. The ONE important thing is to have observed what had not been observed before." I partly agree with the latter part, that observing something new and adding it to the huge knowledge pot (if there's any haha) would be a valuable thing. But, how about the qualitative aspect of research? by saying "quantitative affair" is he denying the value of qualitative study?

# data[].attributes.body
J: I chose to add [The learning of emotion in/as sociocultural practice: The case of animal rights activity] by Tanner Vea, my former advisor!

# data[].attributes.body
1) the discussion of RFP (recommendation for practice) doesn't really make sense to me. It is just a recommendation, what are you expecting to happen from a single study? In my humble view, I think this is just like all paper that needs an implication part to discuss how their findings have practical meaning.

2) the increase of qualitative and decrease of edpsy research. First, it is just %, not absolute value. Second, I don't think this is because quan methods are less popular, it is that certain phenomena can only be investigated by qual methods. Quan and Qual have different ways to reach validity and reliability, but they all care about such attributes. And the author did not discuss how people are doing quals today, compared to decades ago. With reliable computer/app/log data, and with larger amount of participants, the things happening are more prominent than those in the past.