  ChatGPT has shown its great power in text processing, including its reasoning
ability from text reading. However, there has not been any direct comparison
between human readers and ChatGPT in reasoning ability related to text reading.
This study was undertaken to investigate how ChatGPTs (i.e., ChatGPT and
ChatGPT Plus) and Chinese senior school students as ESL learners exhibited
their reasoning ability from English narrative texts. Additionally, we compared
the two ChatGPTs in the reasoning performances when commands were updated
elaborately. The whole study was composed of three reasoning tests: Test 1 for
commonsense inference, Test 2 for emotional inference, and Test 3 for causal
inference. The results showed that in Test 1, the students outdid the two
ChatGPT versions in local-culture-related inferences but performed worse than
the chatbots in daily-life inferences. In Test 2, ChatGPT Plus excelled whereas
ChatGPT lagged behind in accuracy. In association with both accuracy and
frequency of correct responses, the students were inferior to the two chatbots.
Compared with ChatGPTs' better performance in positive emotions, the students
showed their superiority in inferring negative emotions. In Test 3, the
students demonstrated better logical analysis, outdoing both chatbots. In
updating command condition, ChatGPT Plus displayed good causal reasoning
ability while ChatGPT kept unchanged. Our study reveals that human readers and
ChatGPTs have their respective advantages and disadvantages in drawing
inferences from text reading comprehension, unlocking a complementary
relationship in text-based reasoning.
