Complex learning theories

Posted on October 27, 2019 by fqantonio

The common about all the following theories is the “Authentic Learning Tasks” that can be resumed by same principles:

(Merril 2001) LEARNING is promoted when…

(a) … learners are engaged in solving real-world problems.

(b) … existing knowledge is activated as a foundation for new knowledge.

(c) … new knowledge is demonstrated to the learner.

(d) … new knowledge is applied by the learner.

(e) … new knowledge is integrated into the learner’s world.

Source: Merrill, M.. (2001). First Principles of Instruction. Educational Technology Research and Development. 50. 10.1007/BF02505024.

THEORIES

4-Mat, 1996, McCarthy;

Cognitive Apprenticeship, 1989, Collins, Brown, Newman;

Cognitive Apprenticeship (Collins, Brown, Newman)

Collaborative Problem Solving, 1999, Nelson;

https://web.cortland.edu/frieda/id/IDtheories/34.html

Construtivism and construtivist learning environments, 1999, Jonassen;

https://web.cortland.edu/frieda/id/IDtheories/33.html

Instructional Episodes, 1997, Andre;

Article Summary: Andre (1997) Microinstructional Methods to Facilitate Knowledge Construction

Learning by Doing, 1999, Schank, Berman, MacPerson;

Learning By Doing

Multiple Approaches to Understanding, 1999, Gardner;

https://web.cortland.edu/frieda/id/IDtheories/19.html

Star Legacy, 1999, VanderBilt Learning Technology Group;

page 8, https://ocw.metu.edu.tr/pluginfile.php/9336/mod_resource/content/1/firstprinciplesbymerrill.pdf

Four-component Instructional Design model, 1997, Merriënboer;

http://web.mit.edu/xtalks/TenStepsToComplexLearning-Kirschner-VanMerrienboer.pdf

Source: Ten Steps to Complex Learning, Merriënboer; Kirschner, 2007;

More:

https://web.cortland.edu/frieda/id/IDdatabase.html

https://edtechbooks.org/pdfs/print/lidtfoundations/_lidtfoundations.pdf

new references

Posted on August 19, 2019 by fqantonio

Learning:

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.96.2854&rep=rep1&type=pdf

http://ac.els-cdn.com/S2212667812001839/1-s2.0-S2212667812001839-main.pdf?_tid=64daf142-832f-11e7-a280-00000aacb35e&acdnat=1502962703_80a57dffa32503636d62133850ce1012

http://paginas.fe.up.pt/~prodei/DSIE08/papers/35.pdf

https://link.springer.com/chapter/10.1007/978-3-319-39690-3_40

https://www.researchgate.net/publication/303761520_Learning_Object_Assembly_Based_on_Learning_Styles

Confirmatory Factor Analysis for Applied Research: Cluster analysis?

http://apps.maksimrudnev.com:3838/MIE/

http://www.kharazmi-statistics.ir/Uploads/Public/book/Methodology%20in%20the%20Social%20Sciences.pdf

Data analysis:

https://open.sap.com/courses/ds1

eLearning: Virtual LearningEnvironment case:

https://rem.rc.iseg.ulisboa.pt/lese/5e3/files/Papers/Learning%20Analytics%20and%20Data%20Topography.pdf

MOOC’s: high dropout!

https://rem.rc.iseg.ulisboa.pt/lese/5e3/files/Papers/planning-prompts_Rzepka.pdf

Learning Styles: evidences?

http://www.leerbeleving.nl/wp-content/uploads/2011/09/learning-styles.pdf

Research: Action Research?

http://digitalcommons.nl.edu/cgi/viewcontent.cgi?article=1107&context=ie

Assessment:

https://educationendowmentfoundation.org.uk/tools/assessing-and-monitoring-pupil-progress/ampp-introduction/

https://www.teachfirst.org.uk/sites/default/files/2017-10/Putting_Evidence_to_work_2017.pdf

data analysis: first thing first

Posted on August 23, 2017 by fqantonio

look at it!
1. What is the format of the data?
2. What are the dimensions?
3. What are the variable names?
4. How are the variables stored?
5. Are there missing data? How much?
6. How are the data distributed?
7. Are there any flaws in the data?

So, procedure steps list:

Check the list the variables set in your R workspace: use ls() to see what variables there are (if you need clear your workspace data set by apply this command: rm(ls()).
Check class of the data set you want to study: class(“name of the data set) (NOTE: It’s very common for data to be “data frame” class. It is the default class for data read.)
Dimensions: use dim(“name of the data set”) to see the data set dimensions: first number are the number of rows, the second, the number of columns.
variables names: names(“name of the data set”)
most of the times the data rows are to much, but you can see the first six rows: apply head(“name of your data set”) (NOTE: if you want to see the first 15 use: head(“name of the data set”, 15)
The same for the bottom of the data set: tail(“name of the data set”)
To see the distribution of your data and the number of missing data: summary(“name of your data set”)???
1. numerical variables
2. factor variables
3. factor/numerical variables
The last but not the least, the function that groups the last steps together, perhaps, the most useful and concise function for understanding your data: str()

More==============

Intro: https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf

Advanced: https://cran.r-project.org/doc/contrib/usingR.pdf