"answer problems" is a correct and usable phrase in written English.
It can be used in a variety of contexts, such as in academic essays, business reports, or everyday communication. One example of using "answer problems" in a sentence could be: "In order to effectively manage a team, a leader must be able to identify and answer problems as they arise."
In the other study, about 120 students were asked to answer problems on a sheet of paper, with the promise of $1 for each right answer.
Higher competition among enterprises demands for more updated information to enable management to rapidly adapt to opportunities and answer problems.
Three companies currently taking part are developing new and innovative products to answer problems ranging from cycling safety on the roads and security in the home to how to make musical instruments more interesting.
The benefits of interleaving study and test opportunities – rather than blocking study followed by attempting to answer problems or questions – might arise due to a process known as "test-potentiated learning".
Low total answer-attempt counts may indicate that the student has sufficient knowledge to answer problems, while high answer-attempt counts may indicate difficulty with the problem or possibly engagement in systematic guessing or gaming behavior (Baker et al. 2004).
Therefore we have put dynamic systems theory of coherently controlled fermions into a Lie-algebraic frame in order to answer problems of controllability, reachability, and simulability in a unified picture.
In addition, what is the answer to this question as a function of problem size and is the answer problem dependent?
EAR uses SES to generate multiple-answer problems with current knowledge edited by the tutor.
Furthermore, because SES is unsuitable for creating small quantities of multiple-answer problems, it is intended for those who want to generate large quantities of multiple-answer problems that can be solved using procedural knowledge.
The fifth paper by Matsuda, Ogawa, Hirashima, and Taki, A Generating Technique and Knowledge Representation of Multiple-Answer Problems for Learning with Solving Knowledge, addressed a method to generate erroneous answers and explanations about the errors in multiple-answer problems.
In establishing a technology for generating multiple-answer problems for learning with meaningful erroneous answers and explanations, this paper suggests employing core technique SES to generate multiple-answer problems according to their solutions using Prolog.
