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How to implement the subjective scoring function of test questions in online answering questions
With the development and popularization of online education, more and more students are beginning to use online answering platforms Practice and test. On these platforms, students often encounter some subjective questions, such as essay questions, writing questions, etc. Scoring these subjective questions is a relatively complex task because it needs to take into account multiple aspects, such as grammar, logic, perspective, etc. In this article, we will explore how to implement the subjective scoring function of test questions in online answering and provide specific code examples.
First of all, we need to clarify the scoring criteria. For subjective questions, the scoring criteria are very important. We can develop a set of scoring rules, including requirements for grammar, logic, perspective, etc. For example, for an essay question, the scoring rubric may include:
Next, we can implement the subjective scoring function by writing code. The following is a sample code for scoring the answers to an essay question:
def evaluate_essay(answer): score = 0 # 评分标准 grammar_score = 0.6 logic_score = 0.8 viewpoint_score = 1.0 # 语法和拼写评分 grammar_errors = check_grammar(answer) grammar_score -= grammar_errors * 0.1 # 逻辑思维评分 logic_score -= check_logic(answer) * 0.2 # 观点表达评分 viewpoint_score -= check_viewpoint(answer) * 0.3 # 加权计算总分 score = grammar_score * 0.4 + logic_score * 0.3 + viewpoint_score * 0.3 return score def check_grammar(answer): # 检查答案中的语法和拼写错误 # 返回错误数量 pass def check_logic(answer): # 检查答案的逻辑思维是否合理 # 返回错误数量 pass def check_viewpoint(answer): # 检查答案中观点的表达是否准确 # 返回错误数量 pass # 测试代码 answer = "在我看来,学习是一种享受,通过学习我们可以不断进步。" score = evaluate_essay(answer) print("得分:", score)
In the above sample code, the evaluate_essay
function accepts an answer as input and then evaluates the answers based on the scoring criteria Score each item and obtain the final score through weighted calculation. Among them, the check_grammar
, check_logic
and check_viewpoint
functions are used to check grammar, logic and viewpoint respectively, and return the corresponding number of errors.
It should be noted that the above code is only an example, and the actual implementation of the scoring function may vary depending on specific needs. For example, more rubrics and more complex scoring rules may be needed, or answers may need to be deeply analyzed using natural language processing technology. Therefore, make corresponding adjustments and expansions according to actual needs.
In summary, implementing the subjective scoring function of test questions requires clarifying the scoring standards and writing corresponding code to implement the scoring logic. In actual development, further optimization and expansion can be carried out according to specific requirements to make the scoring results more accurate and reliable.
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