How to implement the test difficulty adaptive function in online answering questions

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Release: 2023-09-27 06:00:01
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How to implement the test difficulty adaptive function in online answering questions

How to implement the question difficulty adaptive function in online answering questions

With the rise of online education, more and more learners choose to study on the Internet. Online question answering is a very important part, and its question difficulty adaptive function plays a crucial role in improving learning results. This article will introduce how to implement the question difficulty adaptive function in online question answering and provide some specific code examples.

The key to realizing the test difficulty adaptive function is to dynamically adjust the difficulty of the test questions according to the learner's ability level. An adaptive algorithm for test question difficulty based on learners' responses will be introduced below.

  1. Determine the difficulty level of the test questions
    First, you need to divide the test questions into different difficulty levels, such as easy, medium and difficult. The difficulty level of the test questions can be determined based on the characteristics of the test questions such as knowledge points, question types, and problem solving ideas. Different difficulty levels of test questions can correspond to different score ranges.
  2. Assess the learner’s ability level
    Before the learner starts answering questions, his or her ability level needs to be assessed. Assessment can be obtained through learners’ historical answer data, scores or special tests. Some common ability assessment methods can be used, such as ranking method, percentile method or IRT (Item Response Theory).
  3. Select test questions based on the learner’s ability level
    Choose test questions that are suitable for the learner’s ability level. For example, for weak learners, you can choose easy difficulty test questions; for strong ability learners, you can choose medium or difficult difficulty test questions. You can use a calculation formula to calculate the score range of the test questions based on the learner's ability level and the difficulty level of the test questions, and then select the test questions based on the score range.

The following is a sample code of the test question difficulty adaptive function to briefly illustrate the above implementation idea:

def get_difficulty(level, ability): # 定义试题难度与得分范围的关系 difficulty_range = { "easy": (0, 3), "medium": (4, 7), "hard": (8, 10) } # 根据能力水平和试题难度等级计算试题分数范围 min_score = difficulty_range[level][0] max_score = difficulty_range[level][1] difficulty_score = min_score + (max_score - min_score) * ability return difficulty_score def select_question(questions, ability): # 根据学习者能力水平选择试题 selected_question = None max_score = 0 for question in questions: difficulty = question["difficulty"] difficulty_score = get_difficulty(difficulty, ability) if difficulty_score > max_score: max_score = difficulty_score selected_question = question return selected_question # 测试代码 questions = [ {"id": 1, "difficulty": "easy", "content": "问题1"}, {"id": 2, "difficulty": "medium", "content": "问题2"}, {"id": 3, "difficulty": "hard", "content": "问题3"} ] ability = 0.8 selected_question = select_question(questions, ability) print(selected_question)
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In the above code, theget_difficultyfunction is based on The test question difficulty level and learner ability level are used to calculate the score range for the test question.select_questionThe function selects appropriate test questions based on the learner’s ability level.

In practical applications, the above code needs to be embedded into the online question answering system, and appropriately adjusted and expanded according to actual needs. In addition, machine learning and other technologies can also be combined to optimize and improve the question difficulty adaptive algorithm.

To sum up, implementing the test difficulty adaptive function in online answering mainly requires determining the difficulty level of the test questions, assessing the learner's ability level, and selecting test questions based on the ability level. By dynamically adjusting the difficulty of test questions, it can better meet the needs of learners and improve learning effects.

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