NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 5 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Kaltcheva, Nadia; Nenkova, Maia – Physics Education, 2021
Many introductory astronomy courses include concepts related to basic stellar properties. In general, these are concepts that originate from the human perception of starlight. This observational aspect is not easy to incorporate in the classroom. We explore if these concepts could be developed using the built-in data in a planetarium software.…
Descriptors: Teaching Methods, Introductory Courses, Astronomy, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Rossi, Sabrina; Giordano, Enrica; Lanciano, Nicoletta – Physics Education, 2015
Many researchers have documented the difficulties for learners of different ages and preparations in understanding basic astronomical concepts. Traditional instructional strategies and communication media do not seem to be effective in producing meaningful understanding, or even induce misconceptions and misinterpretations. In line with recent…
Descriptors: Physics, Science Education, Earth Science, Astronomy
Peer reviewed Peer reviewed
Direct linkDirect link
Walker, Justin – Physics Education, 2010
The benefits of using data logging to teach "how science works" are presented. Pedagogical approaches that take advantage of other school ICT are briefly described. A series of simple, quick experiments are given together with their resulting charts. Examples of the questions that arise from the charts show how the rich data lead to the refinement…
Descriptors: Science Instruction, Physics, Laboratory Equipment, Water
Peer reviewed Peer reviewed
Barnes, Howard – Physics Education, 2000
Teaches data interpretation using the example of world running records for men and women. Explains different ways of plotting data. (YDS)
Descriptors: Data Analysis, Graphs, Physics, Science Education
Peer reviewed Peer reviewed
Phillips, M. D. – Physics Education, 1972
Classifies experimental error into two main groups: systematic error (instrument, personal, inherent, and variational errors) and random errors (reading and setting errors) and presents mathematical treatments for the determination of random errors. (PR)
Descriptors: Data Analysis, Error Patterns, Evaluation Methods, Experiments