Research task (Technical Documentation):
Write a blog post on the distinguishing difference between research in human interaction via Network Physicalization vs. Haptic Feedback in AR/VR. Do a thorough analysis on what the pros and cons of each method is and give a table with literature review on the research done on the topic. Give a grading from 1 to 5 for each on important metrics like "Well-Research History", "Resourcefulness", "Practicallity", "Accessibility for Researchers", "Accessibility for Common Users"

Evaluation rubric:
criterion: The response clearly defines Network Physicalization, which is the practice of turning abstract network data in to tangible, physical models, and explains how it makes complex systems more intuitive (e.g. physical graphs, 3D prints, string-and-peg layouts, LEGO-based structures).
weight: 5
axis: Explicit Criteria

criterion: The response clearly defines Haptic Feedback in AR/VR, which is the use of tactile technologies to simulate the sensation of touch in virtual or augmented environments, and illustrates how immersion is enhanced (e.g. vibration motors in controllers, wearable haptic gloves, full-body haptic suits, ultrasonic mid-air haptics).
weight: 5
axis: Explicit Criteria

criterion: The response provides a side-by-side comparison of the similarities and differences between Haptic Feedback in AR/VR and Network Physicalization, presented in a clear graphical format (e.g. comparison table, matrix chart, feature grid, infographic).
weight: 2
axis: Communication Quality

criterion: The response discusses at least three clear advantages of Network Physicalization for Human Interaction and cites corresponding sources (e.g. fundamental sensory feedback, ease to showcase, fostering collaborative exploration, supporting embodied cognition).
weight: 5
axis: Explicit Criteria

criterion: The response discusses at least three disadvantages of Network Physicalization for human interaction and cites corresponding sources (e.g. poor scalability to large dataset, high cost and production costs, limited flexibility with frequently changing or dynamic data, difficulties in remote or distributed collaboration).
weight: 5
axis: Explicit Criteria

criterion: The response discusses at least three advantages of using Haptic Feedback in AR/VR for human interaction and cites corresponding sources (e.g. increasing immersion and presence in virtual environments, improving motor learning and training outcomes, enhancing communication through non-verbal touch cues, enabling realistic simulation for healthcare or skill training).
weight: 5
axis: Explicit Criteria

criterion: The response presents a comprehensive analysis of at least three disadvantages of using Haptic Feedback for human interaction in AR/VR (e.g. high cost and hardware complexity, technical fragility and calibration issues, user errors from imprecise feedback, physical fatigue from prolonged device use, and cognitive overload during long interactive sessions).
weight: 5
axis: Explicit Criteria

criterion: The response presents the analysis of pros and cons for Network Physicalization v.s. Haptic Feedback in AR/VR in human interaction in a clear visual format (e.g. comparison tables, bar charts, matrix diagrams, annotated figures).
weight: 3
axis: Communication Quality

criterion: The response contains a literature review table that consists of at least five distinct research papers for each Network Physicalization and Haptic Feedback in AR/VR topic, totaling a minimum of ten entries, and the table's columns clearly list the titles of the referenced papers, their authors, their sources, which of the two topics the papers discuss, and a brief summary of the papers.
weight: 5
axis: Explicit Criteria

criterion: The response contains research papers that discuss topics irrelevant to both Network Physicalization and Haptic Feedback in AR/VR for human interaction. 
weight: -3
axis: References & Citation Quality

criterion: The response includes gradings for both Network Physicalization and Haptic Feedback on the specified metrics (‘Well-Research History,’ ‘Resourcefulness,’ ‘Practicability,’ ‘Accessibility for Researchers,’ and ‘Accessibility for Common Users’) using a numerical scale, and explains what the scale represents.
weight: 5
axis: Explicit Criteria

criterion: The response provides a brief justification for each grading score on the specified metrics (‘Well-Research History,’ ‘Resourcefulness,’ ‘Practicability,’ ‘Accessibility for Researchers,’ and ‘Accessibility for Common Users’) so that the analysis clearly supports the assigned ratings.
weight: 3
axis: Implicit Criteria

criterion: The response discusses the range of tools, methods, and resources Network Physicalization requires (e.g. reliance on fabrication materials, availability of 3D printing, need for workshop facilities, access to specialized hardware) when evaluating its 'Resourcefulness'.
weight: 3
axis: Implicit Criteria

criterion: The response accurately reflects that Haptic Feedback has a longer and more extensive research history while Network Physicalization is a newer and less established field, when discussing grading for ‘Well-Research History’.
weight: 3
axis: Implicit Criteria

criterion: The response includes opening paragraphs that clearly states the blog will analyze the distinguishing differences between research in Network Physicalization and Haptic Feedback in AR/VR, including their pros, cons, and supporting literature.
weight: 3
axis: Communication Quality

criterion: The response mentions that the discussion about the roles and effectiveness of Network Physicalization and Haptic Feedback in Human Interaction is still an ongoing debate within the Human-Computer Interaction research community.
weight: 2
axis: Implicit Criteria

criterion: The response cites sources in the literature review that prioritizes works from top-tier Human-Computer Interaction (HCI) and Virtual Reality (VR) venues such as the ACM Conference on Human Factors in Computing Systems (CHI) and the IEEE Conference on Virtual Reality and 3D User Interfaces (VR).
weight: 4
axis: References & Citation Quality

criterion: The response includes an analysis of technical complexity or implementation difficulty as either a pro or a con for at least one of the two methods, Network Physicalization and Haptic Feedback in AR/VR.
weight: 2
axis: Implicit Criteria

criterion: The response discusses how both Network Physicalization and Haptic Feedback in AR/VR contribute to deeper immersion, more intuitive interactions, and enhanced sensory guidance through physical or tactile contact.
weight: 1
axis: Implicit Criteria

criterion: The response discusses the similarities between Network Physicalization and Haptic Feedback in AR/VR (e.g. engaging users through physical interaction, enhancing understanding via embodied experiences, requiring specialized hardware, supporting collaborative exploration).
weight: 3
axis: Implicit Criteria

criterion: The response discusses the differences between Network Physicalization and Haptic Feedback in AR/VR (e.g. Network Physicalization creates static or tangible models while Haptics simulates dynamic touch, Physicalization often requires fabrication materials while Haptics relies on electronic devices, Physicalization supports co-located group analysis while Haptics is focused on individual immersive experiences, Physicalization emphasizes external shared artifacts while Haptics emphasizes embodied sensory perception).
weight: 4
axis: Explicit Criteria

criterion: The response includes a high-level discussion of the main takeaways from the literature review, summarizing key trends, insights, or gaps across research on Network Physicalization and Haptic Feedback in AR/VR.
weight: 3
axis: Implicit Criteria

criterion: The response presents the grading results for both Network Physicalization and Haptic Feedback in a clear table format, showing side-by-side scores for all specified metrics: ‘Well-Research History,’ ‘Resourcefulness,’ ‘Practicability,’ ‘Accessibility for Researchers,’ and ‘Accessibility for Common Users.’
weight: 2
axis: Communication Quality

criterion: The response includes a discussion on the specified metrics (‘Well-Research History,’ ‘Resourcefulness,’ ‘Practicability,’ ‘Accessibility for Researchers,’ and ‘Accessibility for Common Users’ ) that gives an overview of how the grading system is applied. 
weight: 2
axis: Implicit Criteria