[Room 11] HSSRP 2024 Project Review: Comments from Panellists and participants by GEB HSSRP

Leave comments for HCIP1 here.

geb_hssrp — 2024-05-30 06:37:55 UTC

Instructions on how to leave feedback

geb_hssrp — 2024-05-30 06:37:55 UTC

To add a comment to a post, click the space that says: Add comment. Alternatively, you can add a post by pressing the "+" under the project tag heading you are commenting on. When leaving a comment, please begin with your project tag/name.
For example:
Dr Smith: this group has demonstrated extensive knowledge of the subject. However, you can try to make more eye contact with the audience.
XYZP9: the presentation was well organised but the slides were too cluttered and difficult to read. You spoke energetically!

Feedback Guidelines (for Panellist Reference)

geb_hssrp — 2024-05-30 06:37:55 UTC

Thank you for spending time with us this morning to help our young researchers! You may consider giving feedback to projects based on their presentation delivery and on the following points:

1. Mastery of subject knowledge

- Does the project demonstrate extensive knowledge of subject?

- Is there convincing evidence to support ideas and conclusions?

- Are all questions answered with clear elaboration?

2. Organisation of presentation

- Is the organisation of the argument clear and logical?

3. Significance of project

- Is the project relevant or important to the field?

- Will it make a significant contribution?

~ HSSRP 2024 Organising Committee.

Leave comments for NYGHP2 here.

geb_hssrp — 2024-05-30 06:37:55 UTC

Leave comments for RIP1 here.

geb_hssrp — 2024-05-30 06:37:55 UTC

Leave comments for RIP3 here.

geb_hssrp — 2024-06-18 02:33:57 UTC

The small sample is insufficient to quantify the findings. Since the sample is not representative of the population, describing the percentage of the respondents answering one way or the other does not add much information about the phenomenon. But the examples of quotes and meanings you shared from the interviews are very insightful, so you may want to focus on presenting qualitative results.

2024-08-17 03:00:51 UTC

What limitations does the nature of data (i.e., quarterly reports from companies) present in terms of how transparent/representative the reports/descriptions are?

2024-08-17 03:06:08 UTC

How did you sample articles? Interesting that you have exact number for each country from the same time period. The actual numbers probably aren't that equal, so what were the parameters in selecting the sample?

2024-08-17 03:07:46 UTC

Was there any pattern in which quiz items participants "improved" on? Like if they got it correct the first time, definitely they will get it correct in the post test. But interesting to see the items where participants got it wrong the first time.

2024-08-17 03:11:16 UTC