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How is it that https://en.wikipedia.org/wiki/Type_theory links to https://en.wikipedia.org/wiki/Type_(model_theory) but the latter does not have any link to or mention of https://en.wikipedia.org/wiki/Type_theory

Neither mentions the relationship between them, but both of them should, since I expect that is a common question.

Jones, M. I., Sirianni, A. D., & Fu, F. (2021). Polarization, Abstention, and the Median Voter Theorem. ArXiv:2103.12847 [Physics]. http://arxiv.org/abs/2103.12847

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Baker, C. M., Campbell, P. T., Chades, I., Dean, A. J., Hester, S. M., Holden, M. H., McCaw, J. M., McVernon, J., Moss, R., Shearer, F. M., & Possingham, H. P. (2020). From climate change to pandemics: Decision science can help scientists have impact. ArXiv:2007.13261 [Physics]. http://arxiv.org/abs/2007.13261

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no

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gambar model yang sederhana. akan bagus kalau kita dapat menggambarkan sendiri (walaupun hanya dengan tangan) interaksi yang sama di daerah kita.

Fogg Behavior Model says that for a Behavior (B) to occur 3 things have to be present at the same time:

1. Motivation (M)
2. Ability (A)
3. Trigger (T)

B = MAT

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Soderberg, C. K., Errington, T., Schiavone, S. R., Bottesini, J. G., Thorn, F. S., Vazire, S., Esterling, K. M., & Nosek, B. A. (2020). Research Quality of Registered Reports Compared to the Traditional Publishing Model. MetaArXiv. https://doi.org/10.31222/osf.io/7x9vy

when using [[dbt]] the [[transformations]] are [[SQL statements]] - already something that our team knows

[[positional attribution]] works by identifying the touch points in the lifecycle, and dividing up the points across those touches.

There are four main ways to divvy up this pointing

[[question]] What are the four main ways to divvy up positional attribution]]

• [[first touch]]
• [[last touch]]
• [[fourty-twenty-fourty]]
• [[linear]]

[[1. Gather your required data sources]] - once we have data, we need to do two things [[sessionization]] - the aggregation of pageviews / etc into a session

and [[user stitching]] - when we have a user without any identifying information, and then converts - kind of like the anonymous users / signups - and trying to tie them back to a source

[[1. Gather your required data sources]]

[[How to build an attribution model]]

• [[1. Gather your required data sources]]
• [[2. Find all sessions before conversion]]
• [[3. Calculate the total sessions and the session index]]
• [[3. Allocate points]]
• [[4. Bonus Join in revenue value]]
• [[5. Bonus Join with ad spend data]]
• [[6. Ship it!]]

One of the goals of an [[attribution data model]] is to understand why someone [[converted]] to being a customer. This is impossible to do accurately, but this is where analysis comes in.

There are some [[approaches to attribution]], one of those is [[positional attribution]]

[[positional attribution]] is that we are weighting the importance of touch points - or customer interactions, based on their position within the customer lifetime.

[[transparent attribution model]]

[[flexible attribution model]]

[[cheapest attribution model]]

to build an [[attribution model]] we need the raw data - this raw data should capture the [[customer interactions]], and in our case - also partner interactions, or people working with the partner?

Wunderling, N., Krönke, J., Wohlfarth, V., Kohler, J., Heitzig, J., Staal, A., Willner, S., Winkelmann, R., & Donges, J. F. (2020). Modelling nonlinear dynamics of interacting tipping elements on complex networks: The PyCascades package. ArXiv:2011.02031 [Nlin, Physics:Physics]. http://arxiv.org/abs/2011.02031

ORWG Virtual Meeting 08/09/2020 https://www.youtube.com/playlist?list=PLOA0aRJ90NxvXtMt5Si5ukmR9LYfvDueB (n.d.)

The authors discuss the issue of community and engagement in online graduate programs. They carried out a small case study and used a Cognitive Apprenticeship Model to examine a successful program in Higher Education. They found that students feel too many online classes are just reading and writing, regurgitating rather than applying, and lack sufficient connection with the instructor and with other students, They recommend some strategies to fix that, but admit that more work is needed. 9/10

Fostering self-directed learning through strategy is discussed by Bailey et al. (2019) in chapter 1 of “Self-Directed Learning for the 21st Century: Implications for Higher Education.” The authors review the changing role of the educator and the learner based on respective self-directed teaching strategies (problem-based learning, cooperative learning, process-oriented learning) and the learner’s propensity for self-directed learning. In addition to providing principles to promote self-directed learning, the Grow and Borich models for implementing said learning were briefly reviewed. 8/10

The author, Kendra Grant, is the Director of Professional Development and Learning for Quillsoft in Toronto Canada. Grant helps business succeed in education design and support. In this article Grant discusses how quickly the learning environment has changed through technological development. Grant explores the RAT Model, which guides instructors in the "use of technology to help transform instructional practice." Grant then examines the Community of Inquiry model, which seeks to create meaningful instruction through social, cognitive and teaching presence. Grant concludes by providing general principles for creating a positive video presence.

Rating: 8/10

Grimm, V., Johnston, A. S. A., Thulke, H.-H., Forbes, V. E., & Thorbek, P. (2020). Three questions to ask before using model outputs for decision support. Nature Communications, 11(1), 4959. https://doi.org/10.1038/s41467-020-17785-2

Sia, S. F., Yan, L.-M., Chin, A. W. H., Fung, K., Choy, K.-T., Wong, A. Y. L., Kaewpreedee, P., Perera, R. A. P. M., Poon, L. L. M., Nicholls, J. M., Peiris, M., & Yen, H.-L. (2020). Pathogenesis and transmission of SARS-CoV-2 in golden hamsters. Nature, 583(7818), 834–838. https://doi.org/10.1038/s41586-020-2342-5

Karatayev, Vadim A., Madhur Anand, and Chris T. Bauch. ‘Local Lockdowns Outperform Global Lockdown on the Far Side of the COVID-19 Epidemic Curve’. Proceedings of the National Academy of Sciences 117, no. 39 (29 September 2020): 24575–80. https://doi.org/10.1073/pnas.2014385117.