Entropy Video Analysis Summary of Findings

Overview

Videos search was performed by various team members using the following search terms:

  • Entropy 
  • Entropy changes in reactions
  • Entropy chemistry explained
  • Entropy and the second law of thermodynamics
  • Entropy and energy distribution
  • Entropy change chemical reactions
  • Entropy, chemistry, concept

Using these search terms we identified 28 conceptually focused videos that were under 15 minutes and in English. Videos mainly focusing on entropy calculations with no conceptual elements were not considered. We usually limit videos to those with  >100,000 views; however, six videos with fewer than 100,000 views were included in the first pass analysis due to the small number of videos available. We identified several common topics within videos. This included 1) defining entropy in terms of matter and energy distribution in a system, 2) entropy change of reactions, mixing, and phase changes, 3) the 2nd law of thermodynamics, and 4) how entropy drives spontaneity of reactions. After an initial review of the 28 videos, seven were found to either focus more on entropy calculations or did not have enough of a chemistry focus and thus were eliminated from our sample. The remaining 21 videos were coded in depth by 2 faculty and 6 undergraduate students. All members had input on final video consensus. As a result of the in-depth coding, one additional video was eliminated as it focused more on reversible and irreversible processes as opposed to entropy.  

Of the 20 remaining coded videos, 13 (65%) covered the 2nd law, nine (45%) only presented entropy as a measure of randomness, eight (40%) included a phase change, and six (30%) specifically addressed the idea of microstates. It was interesting to note that the 2nd law and entropy as randomness often appeared together in videos and that a focus on entropy as randomness was much more likely to be found in videos that were posted in 2017 or earlier whereas a focus on microstates or the inclusion of phase changes were much more likely to be found in videos posted in 2021 or later. Compared to other video topics, entropy videos had a greater percentage of 3D-Learning elements and Johnstone’s triangle, with energy being the dominant CI and CMR. Compared to the average video, macroscopic and particulate were almost twice as common (95% vs 51% and 75% vs 47%.) For 3D Learning elements, CI, SP, and CMR were all ~15% points higher than the average video. Videos mostly approached entropy from the perspective of physical chemistry, often using Boltzmann’s equations and microstate models, or from a general chemistry perspective, often using intuitive real-world examples to show irreversible processes or entropy driven processes such as dye spontaneously dispersing in water.

  • Summary Table – could be by JT (see Lucian’s) or By date (newer at bottom).

Patterns

What is most unique about the Entropy videos was their high rate of inclusion of macroscopic representation, at 19/20 (95%). This is notably higher than for other topics which ranged from 18% (bonding) to 71% (gases) having macroscopic representations. This may be because entropy is generally a more abstract concept (due to easy misunderstandings and misinterpretations), and therefore examples are considered more important to facilitate comprehension. Specifically, macroscopic examples can provide the visual representation that entropy lacks, as entropy is not directly observable. On the other hand, only 15/20 (75%) of videos contained a symbolic representation. This is a different trend than observed for other topics. For all other topics except Gases, all the videos contained symbolic representations. For Gases, 96% of the videos (all but one) contained symbolic representations. Entropy videos were also relatively high compared to other topics in terms of 15/20 (75%) having particulate representations and with the videos making connections between two or more of the Johnstone’s Triangle elements, 14/20 (70%). 

15/20 (75%) videos contained at least one core idea. Core ideas were the most common 3D Learning Elements present, compared to 55% for Science Practices. Additionally, if CMR was present, so were both Core Ideas and Science Practices.

Interestingly, it was noted that more recent videos, particularly those since 2021, contained more 3D elements than older videos. When identifying trends amongst CI specifically, shorter videos (under 10 minutes) often did not fully meet the criteria for CI. For videos with CIs, Energy was the most commonly presented CI (12/15) with the Particulate Nature of Matter (7/15) and Change and Stability (5/15) present less frequently. Interestingly, 8/10 videos with analogies also contained CIs. Of the 15 videos with CIs, 11 also contained a SP. The specific SPs were varied, with six videos including Developing and Using Models, six  videos including Constructing Explanation, and four videos including Mathematical and Computational Thinking. 

We identified eight videos that addressed Causal Mechanistic Reasoning (CMR). To be considered to include CMR videos must explain a phenomena addressing both the how and why at a level below that of the phenomena. In chemistry this generally means at the particle level. We found that videos that contained CMR addressed one of three questions:

  • What causes entropy changes in systems? 
  • What is the effect of molecular complexity on entropy? 
  • What is the role of entropy in causing chemical/physical processes to occur?  

The most prevalent was explaining entropy changes in systems with respect to changes in temperature, the number of particles in the system, or phase changes (⅝).

The videos that did not contain 3D elements were from channels that do not focus solely on chemistry. These channels included Ted-Ed, The Royal Institution and Science Asylum. These videos provide more of a general overview of the topic and kind of advertise the topic as we discussed in a meeting with rather than focus at a level of depth typical for classroom learning. These videos tend to introduce the concept rather than provide in depth explanations or address the principles of entropy. Videos like Ted-Ed and The Royal Institution explain the concept in a visual appeal, and fail to focus on demonstration.

  • What patterns do we note for Core Ideas?
    • How many of each? Are there ones that are not addressed? 
  • What patterns do we note in Science Practices?
  • What patterns do we note in CMR? 
    • How many of each? Are there ones that are not addressed? 
  • Are there any connections between any of these? 
  • Do the types of videos have connections with Core Ideas?
  • What patterns do we note?
    • Category(ies) that are mostly high? Mostly Low?
    • Are there typical things that drive low ratings?

Overall, the entropy videos showed moderate alignment with the multimedia learning principles. Nearly half (9/20) of the videos were rated highly for multimedia, often incorporating verbal explanations paired with supporting visuals. Similarly, segmenting was rated high in 10 out of 20 videos, with clear sections headings, guiding questions, or summaries helping to structure the content. A large majority (70%) used minimal on screen text, favoring bullet points over full sentences, which helped highlight key ideas without overloading the learner with information. The weakest multimedia element was coherence, with only 35% of the videos avoiding common distractions. These distractions most often included the instructor being visible on screen throughout the video, and the use of background music or unrelated graphics. 

  • Are there common misleading elements or content issues? 

Out of the 20 coded entropy videos, 40% (8/20) were found to have misleading elements or scientific inaccuracies. Misleading elements were found in 30% (6/20) of the analyzed videos and scientific inaccuracies were present in 10% (2/20). A video was classified as having a misleading element if the information could be misinterpreted by viewers. A common example of a misleading element included using a messy room as an analogy to understand entropy as increasing in disorder over time. While this analogy appeared in 20% (4/20) of videos, it was not classified as misleading when the speaker clarified that the analogy could be misinterpreted or was inaccurate. Therefore, the analogy was found to be misleading in 33% (2/6) of videos, where it was presented and not debunked. 

A video was classified as having a scientific inaccuracy if it contained an incorrect statement about entropy. The two inaccuracies noted were misstating the Standard Temperature and Pressure (STP) or incorrectly claiming that energy is stored in chemical bonds. When comparing entropy videos to previously analyzed topics, entropy videos shared a 30% average of containing misleading elements. When comparing scientific inaccuracies/errors, entropy videos had less errors (10%) than other topics on average (23%). Another significant finding was the use of analogies to explain entropy. 60% (12/20) of entropy videos included an analogy, which is much higher than the average of previous topics at 24%. An explanation for this could be due to entropy’s abstract nature compared to previous topics. 

All 20 videos included captions. 50% (10/20) were fully captioned with no issues, 30% (6/20) had auto captions, 10% (2/20) had incorrect/no capitalization, and 10% (2/20) had captions cut out for a portion of the video. When comparing the analyzed entropy videos to previous topics, captions cutting out had not been a significant problem before this topic.